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Interaction Studies 13:3 (2012), –. doi 10.1075/is.13.3.06froissn 1572–0373 ⁄ e-issn 1572–0381 © John Benjamins Publishing Company

Getting interaction theory (IT) together

Integrating developmental, phenomenological, enactive, and dynamical approaches to social interaction

Tom Froese & Shaun GallagherUniversity of Tokyo, Japan / University of Memphis, USA

We argue that progress in our scientific understanding of the ‘social mind’ is hampered by a number of unfounded assumptions. We single out the widely shared assumption that social behavior depends solely on the capacities of an individual agent. In contrast, both developmental and phenomenological studies suggest that the personal-level capacity for detached ‘social cognition’ (conceived as a process of theorizing about and/or simulating another mind) is a secondary achievement that is dependent on more immediate processes of embodied social interaction. We draw on the enactive approach to cognitive science to further clarify this strong notion of ‘social interaction’ in theoretical terms. In addition, we indicate how this interaction theory (IT) could eventually be formalized with the help of a dynamical systems perspective on the interaction process, especially by making use of evolutionary robotics modeling. We conclude that bringing together the methods and insights of developmental, phenomenological, enactive and dynamical approaches to social interaction can provide a promising framework for future research.

Keywords: theory of mind; cognitive science; phenomenology; embodied cognition; dynamical systems theory; enactive approach; social cognition; interaction theory; evolutionary robotics

1. Introduction

The problem of what has become known as ‘social cognition’ or ‘theory of mind’ (ToM) in cognitive science concerns how we normally understand each other in our everyday encounters (C. D. Frith 2008). The traditional debate about how best to explain this capacity has been focused on the use of theoretical inference and/or mental simulation (Carruthers & Smith 1996; Davies & Stone 1995). On some ‘theory theory’ (TT) accounts, social cognition primarily involves belief-desire

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inference based on implicit ‘folk psychology’ (Nichols 2003) or a subpersonal ‘Theory of Mind Mechanism’ (ToMM) instantiated in a neural ‘module’ ( Leslie, Friedman & German 2004). Alternatively, the discovery of so-called ‘mirror neurons’, which activate both when an action is performed by the subject and when that subject observes that action being performed by another agent ( Rizzolatti, Fadiga, Gallese & Fogassi 1996), has inspired some versions of ‘simulation theory’ (ST) to propose a unified explanation of social cognition in terms of a ‘mirror neuron system’ (Gallese, Keysers & Rizzolatti 2004; Keysers & Fadiga 2008). Most recent versions of these approaches to explaining social cognition are therefore united by the following two underlying assumptions.

1. A specific version of methodological individualism which assumes that a per-son’s social cognition is essentially independent of the process of social inter-action1 and is therefore exclusively explainable in terms of that individual’s capacities alone (e.g. belief-desire inference or pretense).

2. A specific version of neuro-reductionism which assumes that the individual’s social cognition is essentially independent of their first-person experience and is therefore exclusively explainable in terms of subpersonal mechanisms alone (e.g. a ToMM and/or mirror neurons).

Effectively, the first assumption shifts the focus of scientific research from the social-interactive domain to the cognitive capacities of an individual person, and the second assumption reduces the cognitive capacities of the individual person to the functioning of their sub-personal brain. Hence, the popularity of the idea of the ‘social brain’ (Adolphs 2009), which integrates TT and ST into a generalized notion of ToM.

This social brain, for humans at least, has a ‘theory of mind’, which enables us to predict what others are going to do on the basis of their desires and beliefs. It also has a ‘mirror system’, which enables us to understand others’ goals and intentions and to empathize with their emotions by a mechanism of motor resonance. (U. Frith & Frith 2010, p. 165)

In what follows we take the phrase ‘theory of mind’ (ToM) to signify in a general way the area of study concerned with ‘social cognition’ as it is typically defined by the two established explanatory approaches in cognitive science, namely ‘theory theory’ (TT) and ‘simulation theory’ (ST). According to the notion of ToM, in this general sense, the fact that we normally understand each other in our every-day encounters can only be explained in terms of subpersonal mechanisms taking place in the mind (or, rather, the brain) of an isolated individual, specifically in terms of so-called ‘folk psychology’, ‘mindreading’ or ‘mentalizing’ and/or neural ‘simulation’.2 Accordingly, the problem of how we normally manage to smoothly


Tom Froese & Shaun Gallagher

interact with each other can only be solved in terms of subpersonal predictions of the other’s behavior. However, this is not the only way to characterize and explain the phenomenon of social understanding.

One promising alternative draws inspiration from the phenomenological tra-dition, which has long been keenly interested in the problem of intersubjectivity (e.g. Husserl [1905–1920] 1973). Phenomenological approaches to cognitive science insist on the primacy of a person’s embodied, interactive, and directly per-ceptual (i.e. not theoretical or explicitly conceptualized) grasp of another’s mind (Zahavi 2001; Gallagher 2001). From this perspective, social understanding first and foremost takes place during our immediate engagement with other people in social interaction, and can in some cases even be constituted by the social interac-tion process itself (De Jaegher, Di Paolo & Gallagher 2010; Gallagher 2008a). This phenomenological perspective has been largely ignored in cognitive science until recently. But some proponents of ToM approaches have started to take an interest in phenomenology, and some have acknowledged that phenomenologists correctly describe aspects of our lived experience (e.g. Buckner, Shriver, Crowley & Allen 2009; Gallese 2005). However, the general reaction is still to dismiss such phenom-enological insights as irrelevant for explaining social understanding, because the essential processes are deemed to be a purely sub-personal affair that is independent of lived experience (e.g. Spaulding 2010; Herschbach 2008; Jacob 2011). In contrast to these strictly dualist approaches, we argue that it is indeed possible for phenom-enology and cognitive science to stand in a reciprocal relationship of ‘mutual con-straints’ or ‘mutual enlightenment’ with each other, so that the insights of one can inform the other and vice versa (Gallagher 1997; Varela 1996; Gallagher & Varela 2003). One aim of this paper is to sketch a possible outline of this mutual partner-ship for the study of social interaction.

First, we briefly introduce the core ideas of the ToM approaches and proceed to discuss some of the challenging experimental evidence that has been discovered by social and developmental psychology. We then indicate how a phenomeno-logically informed theory of social interaction can better account for this empiri-cal data. Although this critical comparison is an important part of the current debate about social cognition, we are keeping this section of the paper relatively brief because most of the arguments have been extensively defended elsewhere ( Gallagher 2012, 2005; De Jaegher, et al. 2010).

The remainder of the paper is dedicated to sketching the outlines of a com-bined phenomenological and enactive3 approach to social interaction, integrated and explicated in terms of dynamical systems theory. We follow the method-ological proposal by Froese and Gallagher (2010) to suggest that the results of agent-based modeling, especially in the context of social interaction, further support this kind of integrated approach. There is a long tradition of relevant



research in social and sociable robotics (Dautenhahn 1994, 1997, 1995; Breazeal 2002). This work is phenomenologically interesting because it is aimed at includ-ing a human participant in the interaction loop of the robot (Dautenhahn 1998; Dautenhahn, Ogden & Quick 2002; Cakmak & Thomaz 2012; for a survey, see Fong, Nourbakhsh & Dautenhahn 2003; for a phenomenological method, see Froese, Suzuki, Ogai & Ikegami 2012). The value of this robotics research has been practically demonstrated by its application to therapy of children with special needs (Robins et al. 2010), including children with autism (Dautenhahn & Werry 2004). Work in humanoid robotics has also indicated that some social action capabilities can develop on the basis of social interaction alone, without the need for explicit theorizing or simulating modules (Mirza, Nehaniv, Dautenhahn & te Boekhorst 2008). However, in this paper we focus our discussion on another kind of synthetic approach to social interaction, which builds on the ‘minimal cogni-tion’ research program in evolutionary robotics (Beer 1995; Harvey, Di Paolo, Wood, Quinn & Tuci 2005). These minimal models demonstrate how dynami-cal systems theory can help to explain underlying sub-personal mechanisms of social interaction in a way complementary to the personal-level phenomenologi-cal understanding of intersubjectivity as embodied and interactive.4

We argue that this integrated approach is a more promising framework for a science of social behavior than the ToM approaches based on methodological individualism and neuro-reductionism:

1. It better accords with personal-level, phenomenological research, rather than dismissing human experience as an irrelevant epiphenomenon;

2. It better accords with recent developmental evidence from early infancy, rather than treating it as insignificant behavior;

3. It better accords with the dynamical and holistic nature of the brain- body-environment system, rather than treating the brain as an isolated ‘black box’ that is inhabited by a ‘belief-desire’ or ‘pretense’ homunculus.

Accordingly, in the following sections we aim to show that this alternative frame-work better matches what is known about human experience, is supported by a comprehensive experimental basis, and can potentially be modeled in a precise mathematical framework.

2. From theory of mind to interaction theory

As indicated above, in cognitive science the study of social cognition has been dominated by a long debate between TT and ST versions of ToM. Recently, the debate has been gradually moving toward hybrid explanations (see, e.g. Goldman



(2006) for a good account). TT, ST, and the various hybrid models all share some of the same assumptions, for example, the assumption that the problem to be addressed concerns ‘mindreading’ – the capacity of being able to understand other persons in terms of their hidden mental states. Note that this assumption depends on a further questionable assumption about how we encounter others, namely in a third-person observational situation where their mental states are primarily hidden from us because they are perceptually opaque (Gallagher 2012). Phenomenological approaches, in contrast, suggest that normally we have a more direct perceptual awareness of other minds without mediation by theory or simulation (Gallagher 2008). Closely aligned with the general ‘mindreading’ assumption is another that we focus on in this paper: the assumption of methodological individualism. Thus, for example, researchers attempt to define the ToMM that would account for an individual’s ability to ‘mindread’ (Leslie et al. 2004), as well as associated internal mechanisms such as an eye-direction detector (EDD), an intentionality detector (ID), etc. (Baron-Cohen 1995). These are hypothesized to be functionalist, sub-personal mechanisms that allow an individual’s brain to access the mental states of the other person in order to better predict, and thereby to control, the other’s subsequent behavior.

Neuroscientific solutions look to ‘mirror neurons’ or specialized ToM areas identified by brain-imaging technologies (Adolphs 2009). Such technologies are in some respects a vast improvement over other ways of studying brain func-tion, but so far they also have suffered from a methodological limitation, which directly reinforces the problem of methodological individualism in the study of social cognition (see, e.g. Schilbach et al. (in press) which documents the impor-tance of these methodological limitations). To be precise, it is not simply that to this point PET and fMRI can only scan one isolated (non-interacting) brain at a time in extremely non-ecological situations (such limitations may be addressed in future technological development), but that in every case neuroscience is confin-ing its investigations to the interior of one (or more) individual heads. This is quite understandable given the subject matter of neuroscience, but precisely for this reason it is not clear that social neuroscience alone will be able to provide the best answers about social processes that may involve something more than just brain processes. For instance, it is possible that some social processes extend through brain, body and environment.

For different reasons ToM theorists have also located and locked their mechanisms inside the individual’s mind. A good example of this is Goldman’s description of the simulation process of mindreading.

A prototypical mind-reading routine of the simulationist type has three main steps. First, the attributor creates in herself pretend states intended to match those of the target. In other words, the attributor attempts to put herself in the


Getting interaction theory (IT) together 1

target’s “mental shoes” […]. The kinds of mental states that can be pretended range across the mental spectrum and include perceptions, desires, beliefs, hopes, plans, sensations, and emotions. The second step is to feed these initial pretend states into some mechanism of the attributor’s own psychology, e.g. a decision-making or emotion-generating mechanism, and allow that mechanism to operate on the pretend states so as to generate one or more new states. […] Third, the attributor assigns the output state to the target […]. (Goldman 2005, pp. 80–81)

We suggest that the problem has been set up in the wrong way, and that it needs to be reframed. It is not clear that providing explanations in terms of internalist-individualist mechanisms is the best way to characterize our everyday interactions with others, or that our everyday understanding involves the attempt to access the other person’s hidden mental states. We now sketch an alternative starting point.

The problem of social understanding is more precisely the problem of how we, as embodied agents (and not just brains), are always already situated in our everyday encounters with others. We find ourselves intersubjectively interacting with those others and understanding them in pragmatic or socially contextu-alized ways, prior to the rare occasions when, for example, we need to give a mental-state explanation for some third party’s behavior or where such behavior, although perceived as goal-directed, escapes our immediate sense-making. In addressing this more general problem of embodied sociality, and in contrast to approaches based on methodological individualism, the fields of developmen-tal psychology, phenomenology, and enactive theory of social interaction have in their own way emphasized the essential role of processes that are not con-fined to the individual, but that are truly interactive. In other words, rather than following the majority consensus according to which social interaction is merely a special case of social cognition (defined as ToM), these alternative approaches argue that, in general, social understanding depends on, and is realized by, social interaction. Enactive theory defines the concept of social interaction in the following way:

Social Interaction: a mutually engaged and co-regulated interaction between at least two autonomous and cognitive agents where the co-regulation and the interactive behaviors mutually affect each other, such that the interaction process constitutes a self-sustaining organization in the domain of relational dynamics. (De Jaegher et al. 2010; see also Froese & Di Paolo 2011a)

Note that this definition is focused on the process of immediate real-time interac-tion with others. It is an interesting open question how it can be extended to include more mediated interactions.5 It is also important to note that an explicit require-ment of social interaction is that the autonomy of the cognitive agents involved is not destroyed, and although its scope can be reduced, it can also be increased.


2 Tom Froese & Shaun Gallagher

In this strict sense, an instrumental relation with a person who is treated as a physical object like any other, as is sometimes assumed by TT approaches (Heal 1986), is not a social interaction according to this definition since in such cases the mutuality of sociality is missing.

This kind of strong notion of social interaction has been central in the phe-nomenological approach to social understanding known as ‘interaction theory’ (IT) (e.g. Gallagher 2001, 2005, 2008a; Gallagher & Hutto 2008; Gallagher & Zahavi 2008). Similarly, according to the enactive approach, the process of social interaction can be manifested in various ways, such as co-determination ( Thompson 2001), participatory sense-making (De Jaegher & Di Paolo 2007), affective ‘inter- enaction’ (Colombetti & Torrance 2009) and mutual incorporation or ‘intercorporeity’ (Fuchs & De Jaegher 2009; Froese & Fuchs 2012). These differences in emphasis need not concern us here. In general, both enactive and IT approaches cite evidence from developmental and social psychology and phenomenology to show that interaction and social contexts are important constitutional factors in social understanding – that is, they are processes and conditions that are not reducible to the individual, but that in themselves have a transformative effect on the individuals who engage and participate in them.

. Evidence for social interaction in infancy and adulthood

This section presents a survey of different sources of evidence that support an enactive and interactive approach to social understanding. An important source of experimental evidence comes from developmental studies in psychology, and there is also evidence to show that social interaction continues to play a funda-mental role in adulthood as well. In addition, we highlight some essential insights of the classical phenomenological research into social interaction.

.1 Social interaction in infancy

To present the full range of evidence in developmental psychology is beyond the scope of this paper (see Reddy (2008) for a good summary). We discuss three phenomena related respectively to the strong notion of social interaction, to the dynamical systems analysis presented in the next section, and to the debate with ToM approaches: neonate imitation, studies of social contingency in interaction, and false-belief tests in infant studies.

Infants, shortly after birth and in some cases less an hour old, have been shown to imitate some of the facial gestures of others (Meltzoff & Moore 1977). There is, however, still some controversy surrounding the interpretation of these studies.



Most developmental psychologists accept that there is at least some phenom-enon here to explain (but see Jones (2009) for dissenting views). Granting that, and granting that neonate imitation is not a reflex (Gallagher & Meltzoff 1996), however, there is no consensus on whether this is genuine imitation, a kind of contagion, a form of perceptual priming, or something else (see Hurley & Chater (2005) and Meltzoff & Prinz (2002) for extensive discussion on these issues).

For our purposes these issues, as well as questions about whether this is the result of pre-natal experience or genetic effects or some combination, can be set aside, since the important point is that the infant comes prepared to interact with others. The interaction into which they enter is not of their own making, or reducible to mirror neuron activation; it depends on another person, and in this case the other actually initiates the process. Nor is it an automatic or mechanical procedure; Csibra and Gergely (2009) have shown, for example, that the infant is more likely to imitate if the other person is attending to her. It is also clear that the infant is not simply a passive spectator trying to figure out what is going on, since the infant is drawn into and actively participates in the process.

IT treats neonate imitation as a beginning point for what Trevarthen (1979) calls ‘primary intersubjectivity’. Primary intersubjectivity involves early develop-ing sensory-motor processes that already characterize the first year of life. During that first year infants consistently engage in second-person interactive processes with others, evidenced by the timing and emotional response of infants’ behavior. Infants “vocalize and gesture in a way that seems [affectively and dynamically] ‘tuned’ to the vocalizations and gestures of the other person” (Gopnik & Meltzoff 1996, p. 131). Developmental studies show the very early appearance of, and the importance of, this timing and coordination in the intersubjective context.6 In ‘still face’ experiments, for example, infants are engaged in a normal face-to-face interaction with an adult for 1 to 2 minutes, followed by the adult assuming a neutral facial expression. This is followed by another normal face-to-face inter-action. Infants between 3 and 6 months become visibly discouraged and upset during the still face period when mutual interaction breaks down (Tronick, Als, Adamson, Wise & Brazelton 1978). The importance of interactive touch has also been demonstrated in the still-person effect (Muir 2002).

In a set of contingency experiments, Murray and Trevarthen (1985) have also shown the importance of the mother’s live interaction with 2-month old infants in their ‘double TV monitor experiment’ where mother and infant interact by means of a two-way live video link. The infants engage in lively interaction in this situa-tion. When presented with a recorded replay of their mother’s actions, however, they quickly disengage and become distracted and upset. This change in behavior occurs even though the visual stimulation has remained the same, although now in the absence of contingency. These results have since been replicated, eliminating



alternative explanations such as infants’ fatigue or memory problems (e.g. Nadel, Carchon, Kervella, Marcelli & Réserbat-Plantey 1999; Soussignan, Nadel, Canet & Gerardin 2006; Stormark & Braarud 2004). We will return to these contingency experiments in the next section.

Secondary intersubjectivity begins with joint attention, during the first year (Trevarthen & Hubley 1978; Reddy 2008). Infants begin to enter into the kinds of interactions with their caregivers that involve jointly attending to objects in prag-matically or socially contextualized situations (Kaye 1982). They learn from others about the value or usefulness of certain objects and actions. They begin to see that another’s movements and expressions often depend on meaningful and pragmatic contexts and are mediated by the surrounding world.

The developmental evidence for the foundational role of social interaction in such contexts has recently been complemented by a new line of experimen-tal evidence, namely spontaneous response tasks which test the ability of young (13–15 mo.) infants to understand false beliefs (see Baillargeon et al. (2010) for a review). In some experiments (e.g. Onishi & Baillargeon 2005; Song, Onishi, Baillargeon & Fisher 2008; Surian, Caldi & Sperber 2007), infants show a ‘ violation of expectations’ (VOE), namely by looking longer at unexpected behavior. For example, an agent has mistaken information (a false belief) about where a toy was left, but they look for it in a location to which it was moved. The infant spends a longer time looking at such behavior. In other experiments (Southgate, Senju & Csibra 2007) infants show ‘anticipated looking’ (AL) at targets where they expect the agent to look for the toy.

Although these new experiments have been consistently designed and inter-preted within the ToM framework (specifically in terms of testing false beliefs), they can be more parsimoniously interpreted from the perspective of strong social interaction. Indeed, on the ToM interpretation, the experimental results are sur-prising since the consensus had been that infants this young do not yet have a concept of belief, and certainly are not capable of representing (or engaging in the kind of ‘metarepresentational’ process necessary to grasp) false belief. But this is exactly what the ToM interpretation forces these theorists to say, i.e. that the infant is engaging in a metarepresentational process of inferential mindreading (e.g. Carruthers 2009). The experimenters follow suit. Indeed, Baillargeon et al. (2010) conclude that the infant not only infers that the agent’s mental state consists of a false belief, but that the child can also reason about a complex set of mental states, including dispositional preferences, intended goals, possession of knowledge about the situation, inferences, and false beliefs.

An alternative hypothesis is that the infant expects the agent’s action to be guided by what the agent has done or seen, about which the infant has per-ceptual knowledge, i.e. the infant has seen the agent in her situation. It seems



possible that the infant has a pragmatic grasp of how perception and action are connected and does not have to infer anything about mental states in order to understand the agent. This view can be taken in a behaviorist direction. Thus, Ruffman and Perner (Ruffman & Perner 2005; Perner & Ruffman 2005) propose an interpretation which appeals to the infant’s grasp of mere behavioral rules (e.g. ‘people look for objects where they last saw them’) gained via statistical learning abilities. This behaviorist interpretation has come under some criti-cism (Baillargeon et al. 2010) because there would seem to be a large number of rules needed to cover the variety of situations to which the infant would be exposed. However, since infants spend their entire first year interacting with others, and begin to engage in joint attention and joint actions starting around 9–12 months, it is not clear why infants should not be able to apply perception and action principles to a variety of situations. Thus, Träuble et al. (2010) sug-gest that the behavioral rules view cannot yet be ruled out, since the rule may be formulated more flexibly or more generally. Alternatively, Povinelli and Vonk (2003) propose a ‘behavioral abstraction hypothesis’ according to which infants (or chimps) can represent abstract categories of behavior and the networks of possible subsequent behaviors and reactions to their own behaviors.

On a more enactive and interactive view, however, the idea that infants are applying perception and action principles can be made sense of without appeal-ing to behavioral rules or representational abstraction processes. On the enactive view, infants understand others in terms of how they can interact with them, or in terms of the infant’s engagement in what the other is doing or expressing or feel-ing. Merleau-Ponty ([1960] 1964, p. 119) once suggested that “the other’s inten-tions somehow play across my body” as a set of possibilities for me to engage in social interaction. Similarly, the other person’s situation, as the infant sees it, offers a set of social affordances for interacting, an enactive principle that applies derivatively to cases where I am simply observing rather than interacting with the agent. Accordingly, what I perceive of the agent’s involvement in the world can influence my expectations (see Gallagher (2012) and Gallagher & Povinelli (2012) for further discussion).

A more interactive experimental paradigm can be found in a study by Buttelmann, Carpenter and Tomasello (2009), where 18-month-olds try to help an agent retrieve a toy while taking into account the fact that the agent doesn’t know about the toy’s switched location. In that situation, when the agent focuses on the wrong location, the infant is ready to lead him to the correct location. But when the agent does know about the switch, and still goes to the original, “wrong” location, the infant goes to assist the agent at that location, suppos-edly with the sense that the agent is doing something different. In this study, in both cases, the agent goes to the same location, but the infant has perceptual



knowledge about what that other agent has previously seen or not seen. This per-ceptual knowledge is sufficient to signal a difference in affordance, i.e. a differ-ence in how the infant can act, and thereby socially interact with the agent. The infant does not have to make inferences to mental states since all of the informa-tion needed to understand the other and to interact, including the apparent aims of the other’s goal-directed behavior, is already available in what the infant has seen of the situation.

Similar results were found in a study by Southgate, Chevallier and Csibra (2010). Here an experimenter hid two toys, each one underneath a separate box, and left the room. While absent, the infant watched as another person switched the contents of the two boxes. On the experimenter’s return she pointed to one of the boxes and announced that the toy hidden inside was a ‘sefo’. Crucially, when the infants were then asked to retrieve the ‘sefo’ most of them approached the other box; they understood that the experimenter had intended to name the other toy, but did not do so directly because she had been unaware of the toy’s changed location. Again, it is not at all clear that the infant engages in some kind of mind-reading since all of this information is available in the perceived situation, and is sufficient to inform the infant’s action.

Generally speaking, while these results are unexpected from the ToM per-spective, they suggest that the capacity for understanding social situations that are complicated by an agent’s lack of information is closely intertwined with the infant’s ability to deploy social competences. They suggest that the infant engages with those situations in a way closer to the perceptual and interaction processes of primary intersubjectivity and joint attention than to metarepresentational and mentalizing abilities.

.2 Social interaction in adulthood

Primary intersubjectivity is not something that disappears after the first year of life. It is not a developmental stage that we leave behind, and it is not, as Currie sug-gests, a set of precursor states “that underpin early intersubjective understanding, and make way for the development of later theorizing or simulation” (2008, p. 212; emphasis added; see also Baron-Cohen 1991; Baron-Cohen 1995). In con-trast, according to the strong notion of social interaction, as well as behavioral and phenomenological evidence, the processes of primary and secondary intersubjec-tivity involved in infancy don’t “make way” for purportedly more sophisticated processes of mindreading – these embodied, situated and interactive processes continue to characterize our everyday encounters even as adults. That is, we con-tinue to understand each other in strongly interactional terms, and this socializing ability continues to be facilitated by our capacity to perceive facial expressions,



hand gestures, bodily postures, and goal-directed actions as meaningful embodi-ments of the other’s mind (see e.g. Krueger 2012; Cuffari in press; Stout 2012).

Scientific experiments bear this out. For instance, close analysis of facial expression, gesture and action in everyday contexts shows that as adults we con-tinue to rely on embodied interactive abilities to understand the intentions and actions of others and to accomplish interactive tasks (Lindblom 2007; Lindblom & Ziemke 2008). The analyses of social interaction in shared activities, in working together, in communicative practices, and so on, show that persons unconsciously coordinate their movements, gestures, and speech acts (Issartel, Martin & Cadopi 2007; Kendon 1990; Lindblom 2007; Oullier, de Guzman, Jantzen, Lagarde & Kelso 2008), entering into synchronized resonance with others, with slight tem-poral modulations (Gergely 2001), in either in-phase or phase-delayed rhythmic co-variation (Fuchs & De Jaegher 2009).

The key idea of a strong notion of social interaction is that the interaction process itself plays an essential role in constituting social cognition (De Jaegher et al. 2010). At the very least, engaging in mutual interaction facilitates mutual understanding. For instance, in communication, as we listen to another person speaking, we spontaneously coordinate our perception-action sequences; our movements are coupled with changes in velocity, direction and intonation of the movements and utterances of the speaker.

. Phenomenology of social interaction

Phenomenology also bears this out. Nevertheless, as we mentioned in the intro-duction, a frequently heard objection is that phenomenology cannot access sub-personal processes, and is therefore irrelevant to explanations of social cognition (e.g. Spaulding 2010). If, however, an individual’s capacity for social understanding cannot be reduced to their internal subpersonal processes, that is, if social under-standing depends also on processes that are best characterized on the first-per-sonal and second-personal levels of explanation, then phenomenology clearly has some relevance (Froese & Fuchs 2012). Furthermore, even if a phenomenological assessment of lived experience is insufficient by itself to make the case for a strong notion of social interaction, the fact that it complements both behavioral and developmental evidence suggests that a combination of phenomenological and enactive accounts may provide a compelling alternative theoretical framework. ToM approaches, on the other hand, lack the coherence offered by an approach to the social which can encompass the first- and third-person perspectives within a unified framework of second-person engagement (Reddy & Morris 2004).

In this spirit, consider Merleau-Ponty’s concept of ‘intercorporeity’. The experimental evidence suggests that from birth the action of the infant and



the perceived action of the other person are coded in the same “language,” a cross-modal sensory-motor system that is directly attuned to the actions and gestures of other humans (Meltzoff & Moore 1997; Gallagher & Meltzoff 1996). In this respect, Husserl ([1905–1920] 1973) offered phenomenological insights as early as 1907 that prefigured the contemporary discussion of neural resonance, namely that our perception of the other person induces a sensory-motor process that reverberates kinetically and kinesthetically with their intentions. Phenomenology thus suggests that in interaction there is a common bodily intentionality that is shared across agents. Merleau-Ponty calls this ‘intercorporeity’, and characterizes it in this way:

“Between my consciousness and my body as I experience it, between this phenomenal body of mine and that of another as I see it from the outside, there exists an internal relation which causes the other to appear as the completion of the system. The other can be evident to me because I am not transparent to myself, and because my subjectivity draws its body in its wake.” (Merleau-Ponty [1945] 2002, p. 410; see also Merleau-Ponty [1964] 1968, pp. 141–143)

Intercorporeity involves a mutual influence of body schemas, but not as Gallese (2009, 2010) suggests, in an isomorphic format, where one maps the other’s actions onto one’s own motor representations. Rather, intercorporeity involves an inter-enactive response to the other’s action; it is taking that action as an affor-dance for further coordinated action, rather than as a cause for internal replication or simulation (Stout 2012). The interaction process temporarily self-organizes the embodiments of the participants into an ‘extended body’ of joint action and emo-tional attunement (Froese & Fuchs 2012). In this way the neuroscientific evidence of ‘mirror’ neurons can be given an enactive interpretation.

To put it simply, the fact that a neural motor system is involved in observing another’s action is astonishing for ToM approaches only because they do not treat social interaction as an essential feature of social cognition. Accordingly, ToM approaches are led to interpret this finding as evidence for subpersonal pretense or neural simulation instead. Alternatively, from the perspective of an enactive approach to perception (e.g. Noë 2004; Varela et al. 1991), it would have been astonishing if there were no motor activity during the perception of other’s actions. For if we accept in general that there is action in perception, then there should be action in social perception, too (Gallagher 2007). The extensive data on ‘ mirror’ neurons can thus be naturally accommodated by an enactive and interactive approach to social cognition: social perception is an active process that is prim-ing us for interaction. This cursory consideration of how to interpret neuronal processes raises the more general issue of developing an alternative framework to subpersonal theorizing.



. A dynamical approach to social interaction

Despite the extensive experimental and phenomenological evidence for the primacy of social interaction over social cognition, some proponents of ToM approaches maintain that when it comes to explaining these findings in terms of subpersonal processes, some version of TT and/or ST is still the only game in town (e.g. Spaulding 2010; Herschbach 2008; Jacob 2011). It is indeed the case that the development of a credible alternative to ToM approaches has so far been mainly focused on clarifying the social phenomena to be explained, i.e. the explanandum, rather than providing an alternative explanans (Zahavi 2011). But since these clar-ifications reveal that the explanandum is significantly different from the way in which it is habitually portrayed by ToM approaches, it seems reasonable to assume that an alternative explanation is required as well. In this final section we sug-gest that the developmental, phenomenological and enactive approaches to social interaction find a natural ally in dynamical systems theory, especially when sup-ported by work in embodied robotics and computer modeling.

.1 Introducing dynamical systems modeling

In its most general sense, dynamical systems theory is a mathematical tool for describing phenomena that change over time. In the context of cognitive science it has been put to a variety of uses (Port & van Gelder 1995). Most importantly, for our purposes, it has been formulated as an alternative to the computational theory of mind (van Gelder 1998), and has enabled the formulation of a research program that views development, behavior and cognition as self-organized properties of a complex system consisting of brain, body and environment (e.g. Smith & Thelen 2003; Beer 2000; Kelso 1995; Rohde 2010).

A potential worry about this dynamical perspective may be that the rejec-tion of the usual subpersonal representationalist explanatory style in favor of a dynamical systems account entails an eliminativist approach to mental phenom-ena. However, this worry only makes sense in the context of a theory that fails to properly take the first-person perspective into account. On the other hand, when it is viewed from a phenomenological perspective, this mathematical framework is seen as one promising bridge between phenomenology and cognitive science (Roy, Petitot, Pachoud & Varela 1999). The key methodological idea is that both experiential and experimental phenomena can be described and interrelated as processes changing in time, thereby avoiding the mind-body problem in practice (Varela 1999; van Gelder 1999). This dynamical approach to phenomenology has been having some success in the context of Varela’s (1996) neurophenomenology research program, which explicitly aims to integrate the dynamics of neural activity



and lived experience in a mutually informing manner (for a review, see Froese, Gould & Barrett 2011).

Nevertheless, one of the limitations of Varela’s original research program is similar to the limitation we identified with current neuroscience more generally, namely a restriction to the activity happening in an individual’s brain alone. But this methodological shortcoming has more to do with the state of neuroscientific technology, and it is desirable to further generalize his dynamical approach to phenomenology to other areas. In a mature research program, it should be possi-ble to include interactions between brain, body and environment, as well as social interaction. Currently, such an undertaking faces considerable methodological challenges, but there are other ways of making progress. For instance, in previous work we argued that it would be helpful to take insights from synthetic approaches to cognitive science into account (Froese & Gallagher 2010). One of the most suc-cessful applications of the dynamical systems approach is the construction of minimalist models of behavior that can inform and challenge our preconceptions (Beer 2003; Harvey et al. 2005). These models, which are optimized by evolution-ary algorithms in order to bracket the designer’s assumptions as much as possible, can serve as a useful technological supplementation of traditional phenomenolog-ical methods. In the case of social interaction, for example, a dynamical systems model of subpersonal processes can help to explain aspects of the phenomenology of intersubjectivity in a way that replaces the explanatory role of the ToM frame-work (Froese & Fuchs 2012).

Accordingly, dynamical systems models can play a similar role for alternative approaches to cognitive science, which symbolic artificial intelligence played for classical cognitive science. The models help to integrate developmental, behav-ioral, phenomenological and enactive approaches in a concrete and practical manner. In the following we introduce the synthetic method in more detail and highlight its application to a well-known problem in interaction studies, namely infants’ sensitivity to social contingency.

.2 Modeling experiments in ‘social contingency’

One popular method of synthesizing dynamical systems models of behavior is the so-called ‘evolutionary robotics’ approach (Harvey et al. 2005). The basic idea is to create a generic dynamical system to serve as a ‘brain’, to embody it in an actual or simulated robot, to situate this ‘agent’ in some task environment, and to use artifi-cial evolution or other optimizing algorithms to automatically shape the structure of the overall brain-body-environment system until it results in behavior that is of scientific interest. A key point is not to restrict the analysis to the agent’s brain, but rather to treat cognition as a relational phenomenon that emerges out of the



nonlinear coupling between brain, body and environment (which could include other agents). This approach is therefore in line with enactive, embodied, embed-ded and extended theories of cognition (Di Paolo, Rohde & De Jaegher 2010). However, due to this holistic, maximally inclusive perspective, the complexity of the overall brain-body-environment system has to be kept to a minimum in order to make an understanding of the agent’s behavior possible. We also note in passing that these agent-based models do not satisfy the biological requirements of an enactive approach to agency in the strict sense (Froese & Ziemke 2009),7 but as models of specific kinds of behavior they serve a heuristic purpose.

In contrast to symbolic artificial intelligence, where the designer directly spec-ifies the behavior and its structural realization, the aim of evolutionary robotics is to keep the designers (and their biases) out of the constructive process as much as possible. Only the desired task should be specified; but not what behavior is nec-essary to accomplish it, and especially not how any behavior is structurally real-ized in the system. In this manner the automatic optimizing algorithm can lead to novel and unexpected kinds of solutions of how best to organize the structure of the artificial agent’s body and/or brain for its task environment. In the most inter-esting cases the solutions probe our intuitions and challenge our preconceptions of the necessary and sufficient conditions for the emergence of the task-solving behavior (Rohde 2010).8

Evolutionary robotics has established itself as a viable method for synthesiz-ing models of what has become known as ‘minimally cognitive behavior’, namely the simplest behavior that raises issues of genuine cognitive interest (Beer 1996). This approach has become notorious for undermining claims about the necessity of certain cognitive mechanisms and mental representations by demonstrating that more minimal, non-representational kinds of processes are sufficient for cognition. For example, it has been shown that associative learning can occur in a neural network without synaptic plasticity (Izquierdo, Harvey & Beer 2008); that categorical perception can occur without discrete inner representations (Beer 2003); that nonreactive behavior can be produced by an agent without internal state (Izquierdo-Torres & Di Paolo 2005); etc. In all of these cases the minimal-ist modeling approach shows that the nonlinear dynamics of an extended brain-body-environment system can, often unexpectedly, be more parsimonious than the kind of mental architecture that is traditionally assumed by cognitivism.

There is also a tradition of using this particular evolutionary robotics model-ing method to investigate the dynamics of social interaction (Di Paolo 2000), or what we could call ‘minimally social behavior’ (Froese & Di Paolo 2011b).9 We will discuss some recent examples of this approach in more detail in a moment. To set these studies into context it should be noted that the field of evolutionary robotics is sometimes criticized for failing to faithfully model real organisms (Webb 2009).



In contrast, we happen to believe that there is value in the use of synthetic approaches for the exploration of more general principles (Froese & Gallagher 2010). Nevertheless, what is especially interesting about some of the evolutionary robotics models of minimally social behavior is that they are directly inspired by psychological experiments. Indeed, they are intended for establishing mutually informing collaborations with the relevant empirical sciences (Rohde 2010).

One popular target has been the ‘minimal perceptual crossing’ paradigm developed by Auvray, Lenay and Stewart (2009). We describe this paradigm in some detail because it further underlines the importance of social interaction. Two participants use a computer mouse and a binary haptic interface in order to locate each other’s avatar in a simple 1D virtual environment, while avoiding being misled by two other objects (a static object and a mobile object that mimics the movements of the other’s avatar as its ‘shadow’). All the objects have the same size and provide the same tactile feedback (tactile feedback is ‘on’ during contact, ‘off ’ otherwise). However, since only the contact between avatars entails that both participants receive feedback, only that kind of contact can result in a mutually responsive interaction. For the task, each participant is asked to respond by mouse click whenever they judge to be in contact with the other’s avatar. The results show that, at least from the perspective of an individual participant, the task is a fail-ure: in terms of the relative probability of clicks for each type of contact (i.e. their likelihood of clicking after contact with the avatar object, the shadow object, or the static object), participants are equally likely to click in response to the other’s avatar and to their shadow. It seems that participants in this study are insensitive to social contingency and/or fail to use it in their judgment. Overall, however, the task is achieved: participants make significantly more correct identifications. This may seem surprising at first, but it can be easily explained in terms of the collec-tive properties of the experimental setup. Participants click correctly more often because they are more frequently engaged with each other than with their respec-tive shadows, because an interaction with a responsive partner is more stable (or attractive) than chasing a non-responsive object.

Without going into the details, we note that evolutionary robotics models of this paradigm have clarified the original empirical data (Di Paolo, Rohde & Iizuka 2008), tested out new variations of the experimental setup (Froese & Di Paolo 2010), and removed confounding factors from the explanation of the original results (Froese & Di Paolo 2011b). Subsequently, there has been another iteration of perceptual crossing experimentation (Lenay & Stewart 2012) and, in response, modeling of the interaction dynamics (Froese, Lenay & Ikegami 2012).

Another popular experimental source of inspiration is the ‘double video’ paradigm mentioned above. In Murray and Trevarthen’s (1985) pioneering study, 2-month-old infants were enticed by their mothers to engage in mutual interaction



via a two-way video link. However, when the live video of the mother was replaced with a playback of her previously recorded actions, the infants quickly became distressed or disinterested in the video, confirming that 2-month-old infants are already sensitive to ‘social contingency’. They can detect whether the other is responsive during an interaction process, and this sensitivity plays an essential role for determining how that process unfolds or breaks down. Most explanations of the infants’ behavior have focused on individual cognitive capacities and sub-personal mechanisms, as is expected from the perspective of ToM approaches. For example, some research in social robotics has been geared toward the implemen-tation of ‘social contingency modules’ (Lee, Chao, Bobick & Thomaz 2012). But is this methodological individualistic approach the only way in which to explain the empirical results?

In order to address this question Iizuka and Di Paolo (2007) used an evo-lutionary robotics approach to test whether simpler solutions for the detection of social contingency could also emerge from the dynamics of the interaction process itself.10 In their simulation model the evolved agents successfully acquired the capacity to discriminate between ‘live’ (two-way) and ‘recorded’ (one-way) interaction. Moreover, a detailed analysis of the resulting behavior suggests that this capacity cannot be reduced to an individual agent, but that the dynamics of the interaction process itself play an essential role. Although Iizuka and Di Paolo specifically evolved their agents to exhibit sensitivity to social contingency, this is not a necessary requirement. Froese and Di Paolo (2008) demonstrated that the playback of recorded behavior during an interaction can spontaneously lead to a breakdown of that process, even if that response has not been selected for by evo-lution. The details of this model need not concern us here, but we highlight some general lessons.

One reason for this spontaneous sensitivity to social contingency is the accumulation of slippage between the behavior of the responsive agent and the behavior of the recorded agent. During a two-way interaction the occurrence of small mismatches in behavior can be mutually renegotiated in subsequent inter-action, while a one-way process sets the recorded agent on a behavioral course that is independent of the other agent or the status of the attempted interaction. Eventually the responsive agent can no longer cope with the growing discrepancy between its behavior and that of the recorded agent; the pseudo-interaction comes to an end. In other words, the agent’s sensitivity can be explained in terms of the fact that two-way coordination of an interaction is more stable than a one-way process, and this implicit sensitivity does not require any dedicated mechanisms of contingency detection. However, one might respond that this explanation does not rule out methodological individualism altogether, because the interaction may simply provide input or scaffolding for what remains essentially an internal



process (see, e.g. the worries raised by Michael & Overgaard 2012; Michael 2011; Herschbach in press).

A more rigorous follow-up study of this model by Froese and Fuchs (2012) has shown this not to be the case. Their dynamical systems analysis of the iso-lated artificial neural network, which controls the movement of an agent’s body, reveals that its activity is organized only by a single globally attracting fixed-point. Since this causes an isolated agent to move with fixed velocity, how is it possible that the agents are able to flexibly regulate their velocity during an interaction to sustain the coordinated movement? It turns out that the internal state of the agent does not go near that attractor during a two-way interaction; rather, it is defined by a semi-periodic trajectory in a transient region of state-space. This internal activity is made possible because the behavior of the other agent modulates the location of the single attractor, and thereby the agent’s behavior, and vice versa, such that the agents co-regulate their behavior in a distributed fashion. There is no methodological individualism here: internal neural activity, individual embodied behavior, and the overall interaction process constrain and enable each other in one distributed system. Moreover, replacing one component of that overall system with another, e.g. by switching one agent with a recorded copy, changes the orga-nization of the overall system and therefore the activity of the other components as well. It is in this overarching systemic context that the corresponding change in the responsive agent’s behavior can be made intelligible. It is beyond the scope of this paper to present more details of this dynamical analysis; the interested reader is referred to the mathematical discussion by Froese and Fuchs (2012).

. Discussion of modeling results

In Froese and Di Paolo’s (2008) model, the agents do not realize their sensitivity to the other’s responsiveness in terms of any internal ToM mechanism, or a ‘social contingency detection module’ (Lee et al. 2012). Instead, their behavior is realized by means of collective properties of the interaction process, thereby demonstrat-ing in principle that it is not always necessary to postulate specialized subpersonal cognitive mechanisms in order to explain the social capacities of an individual. The insights of this dynamical approach are not unique. Other evolutionary robot-ics models of the ‘double video’ paradigm have obtained comparable results (e.g. Di Paolo et al. 2008; Ikegami & Iizuka 2007b; Di Paolo 2000). What are the impli-cations of this kind of modeling study? In what follows we highlight ways in which such a dynamical systems model can help to integrate experimental psychology, enactive theory, and phenomenology into one coherent research program.

First, since the model was inspired by psychological experiments, its insights can help the interpretation of the empirical results. It may be countered that this



kind of model is much too simple to be informative about the social abilities of human infants (Michael 2011, p. 566), but we propose that the argument actually runs the other way. Since we are dealing with a very basic property of coupled sys-tems, it is quite likely that this property will be realized during actual social inter-actions as well. This does not mean that an explanation of actual interaction will be exhausted by this property, but if it comes for free we expect nature to make use of it. Indeed, because infant-mother interaction is so much richer than the mod-eled interaction, we expect that the dynamics of their interaction process will play an even greater role in their behavior. The default assumption should therefore be that, as a starting point, any explanation of a social competence has to include considerations of the potentially constitutive role of the interaction process (a role which, of course, may be refuted on an empirical basis in some cases).

Second, following on from this alternative default assumption, the model nicely supports the enactive theory of social interaction, which holds that the interaction process can self-organize into an autonomous level of dynamics (De Jaegher & Di Paolo 2007). Indeed, it was the distributed interaction pro-cess as a whole which shaped the individual agent’s behavioral response. Given this extended process, there was no necessity for a specialized internal ‘social contingency detection’ module in the agent’s neural controller. The model there-fore questions the plausibility of ToM approaches’ exclusive focus on individualist explanations in the folk-psychological concepts of TT and/or ST. It also questions the plausibility of introducing such personal-level notions into explanations that are situated at the subpersonal level. The model indicates the possibility of an alter-native explanatory framework, which avoids this category mistake, by employ-ing the neutral mathematics of dynamical systems theory (Chemero & Silberstein 2008). The dynamical analysis of the model also has improved our understand-ing of how an interaction process can become a constitutive part of individual agency (De Jaegher & Froese 2009). For instance, we can now venture an enactive hypothesis about neonate imitation: neonates are sensitive to the presence of oth-ers by becoming entrained in a mutually responsive interaction, and their motor schemas are set up in such a way that this kind of entrainment easily re-organizes them for appropriate conduct in an interactively supported manner. From the per-spective of self-organization it is no paradox to say that the behavior of the infants is primed for engaging in interaction by engaging in interaction. This hypothesis is more parsimonious than that of internal dedicated ToM mechanisms because it places less demands on the capabilities of newborns.

Third, although the rejection of ToM approaches in favor of an enactive approach cashed out in terms of dynamical systems theory may increase the worry of a return to some kind of behaviorism (e.g. Jacob 2011), this worry is misplaced. On the contrary, it is mainly proponents of ToM approaches who have



been arguing against the relevance of the first-person experience in cognitive sci-ence. From a phenomenological perspective, a person’s behavior is not the same as an object’s movement; behavior is perceived as an expressive phenomenon already saturated with psychological meaning (Zahavi 2011). In the case of the model, the co-constitution of the behavior of the two agents during their interaction nicely complements an intuition about embodied intersubjectivity, famously expressed by Merleau-Ponty’s notion of ‘intercorporeity’. It has already been observed that this notion is quite compatible with the dynamical systems approach to social interaction (Fuchs & De Jaegher 2009), and here we have a model of how such intercorporeity could operate in practice. As Boden (2006) has remarked, such demonstrations are important because a theory about socially extended minds that can be successfully modeled in a computer isn’t mysterious nonsense. Froese and Fuchs (2012) extend this analysis into a study of the neurophenomenology of social interaction. They suggest that intercorporeity is best conceived as a body that is extended by mutual dynamical entanglement: inter-bodily resonance between individuals can give rise to self-sustaining interaction patterns that go beyond the behavioral capacities of the isolated individuals by modulating their intra-bodily conditions of behavior generation.

. Conclusion

We have argued that the defining assumptions of ToM approaches are in fact unfounded; they are not borne out by careful phenomenological reflection, exper-imental evidence, or by dynamical systems modeling. Accordingly, we suggest that the science of sociality is in need of a methodological and conceptual shift. One promising possibility in this regard is to bring together the insights of enac-tive theory, phenomenological observation, and experimental studies in terms of concepts derived from dynamical systems theory. Using this integrated approach, we have made a two-pronged response to the dominant ToM accounts: (i) we presented empirical and phenomenological evidence for the primacy of embod-ied sociality, which leads more naturally to an interactionist or enactive account, and (ii) we proposed a dynamical systems explanation of strong social interaction based on a concrete model.

Although it has not been our intention to survey or review all relevant approaches to questions that pertain to social cognition, we should point briefly to research in other related areas. In particular, the extended mind hypothesis (Clark & Chalmers 1998; Clark 2008) considers the role of symbolic culture, including language (Clark 2006), but it does not focus explicitly on social inter-action as such (Froese & Di Paolo 2009). Nor is it consistent with the enactive



approach in all aspects (for example, it takes a functionalist approach and down-plays the essential role of embodiment). Whether one can develop a more enac-tive version of the extended mind hypothesis is currently being actively debated (see, e.g. Di Paolo 2009a; Gallagher 2011; Thompson & Stapleton 2009; Wheeler 2010; Noë 2009). One can, however, easily find support for a more interactive approach to social cognition in discussions that link the extended mind with concepts of socially distributed cognition, shared intentions, team cognition and the role of norms and institutions in such contexts (e.g. Fiore, Elias, Gallagher & Jentsch 2008; Gallagher, in press; Hutchins 2010; Steiner & Stewart 2009; Di Paolo 2009b).

Rather than a comprehensive review article that would provide a more his-torical and contemporary survey of the field, we have presented a focused argu-ment in support of an enactive phenomenological approach to social cognition that emphasizes the role of social interaction. The main advantages of focusing research on social interaction are:

1. the role of social interaction accords with the phenomenology, while ToM is forced to discard lived experience as epiphenomenal;

2. the role of social interaction accords with the developmental evidence, while ToM is forced to discard early embodied interaction as ‘mere’ behavior;

3. the role of social interaction accords with dynamical systems theory, while ToM is forced to use homuncular concepts at the subpersonal level.

All in all, we find no convincing reason to favor a ToM approach to social cog-nition from the perspective of phenomenology or empirical evidence. A theory that assigns primacy to social interaction, as outlined in this article, is compelling by overall coherence and parsimony. It can potentially integrate developmental, phenomenological, enactive, and dynamical approaches into a unified research program. Importantly, by emphasizing the role of the first-person perspective, and by using dynamical systems theory to integrate its insights with the rest of cogni-tive science, this approach promises to overcome the mind-body problem and to reconnect science with our immediately lived existence.

Acknowledgements

Tom Froese’s research is supported by a Grant-in-Aid awarded by the Japanese Society for the Promotion of Science (JSPS). Shaun Gallagher’s research is supported by the Marie-Curie Initial Training Network, “TESIS: Towards an Embodied Science of InterSubjectivity” (FP7-PEOPLE-2010-ITN, 264828), and the Humboldt Foundation Anneliese Maier Research Award.



Notes

1. This definition of ‘methodological individualism’ is somewhat different from the way in which Weber, Hayek, Popper and others have used the concept in sociology (Heath 2011). Here we follow Boden (2006) in using the concept to characterize the central working assumption of the cognitivist approaches to social cognition. See Chemero and Silberstein (2008) for a more general discussion.

2. As indicated by Frith and Frith’s (2010) characterization of the ‘social brain’, some ver-sions of ST prefer to describe the neural ‘mirror system’ in terms of ‘motor resonance’ rather than ‘simulation’, but the goal is still a theory of ‘mindreading’ committed to the assumptions of methodological individualism and neuro-reductionism (e.g. Agnew, Bhakoo & Puri 2007). See Froese and Fuchs (2012) for an alternative account of motor resonance in the context of social interaction, which rejects these assumptions.

. The enactive approach to mind and cognition is prefigured in older traditions at least as far back as the empiricists, such as Hume (Froese 2009). Key ideas are also found in certain pragmatists, like Dewey, the phenomenologists, especially Merleau-Ponty, and ecological psychologists like Gibson. In the philosophy of biology there are precursors in Kant, von Uexküll and Jonas (Froese & Ziemke 2009). The locus classicus of enaction, however, is Varela, Thompson and Rosch (1991). They include an important discussion of intersubjectivity. Noë (2004) provides a compelling case for enactive perception, but ignores the intersubjective dimension (Gallagher 2008b; but see Noë 2009). Also see Hutto and Myin (in press) for an enactive critique of the more traditional computational accounts of cognition.

. Some work in cognitive robotics, especially in the area of machine consciousness, investigates – or even attempts to realize – a first-person perspective for artificial ‘agents’. We do not agree with this approach. In our view, biological autonomy is necessary for sense-making (Froese & Ziemke 2009) and genuine first-person experience. It is therefore misleading to treat the computational analysis of meaningless data structures as if it were phenomenology.

. It is possible that the ‘cognitive gap’ between basic social interaction and sophisticated social cognition could be addressed by taking the constitutive role of sociality into account (Froese & Di Paolo 2009). On the other hand, the necessary kind of constitution may depend on an appropriate socio-cultural background (Steiner & Stewart 2009), including narrative practices (Gallagher & Hutto 2008). For proposals of how to bridge between these levels of description, see (Froese & Di Paolo 2011a) and (Torrance & Froese 2011)

. Indeed, intercorporeal interaction likely predates strictly personal-level intersubjectivity and can be traced to prenatal experience and the non-conscious motor coupling between mother and fetus (Lymer 2011).

. The enactive approach to AI in a broad sense emphasizes the role of embodiment and interaction for cognition, but it treats organisms and robots as different in degrees, not in kind (Dautenhahn et al. 2002). A stricter enactive approach insists that living beings are orga-nized in a fundamentally different style than robots, and that this has important implications for cognition (Froese & Ziemke 2009). The debate about whether to synthesize real robots or computer models of robots is an old one (Steels 1994). The choice to study interaction dynamics in models of minimal cognition is not a rejection of embodiment. On the contrary,



it is based on a deliberate recognition that we currently do not have the means to formalize and synthesize the organization of the living (Beer 1997). Running a model on a robotic plat-form rather than in a computer simulation makes no difference in this case.

. This evolutionary, dynamical and holistic approach is quite different from the enac-tive approach to AI in the broad sense. The former takes the dynamics of a whole brain-body-environment system as its starting point, which requires minimalism to make it tractable (Beer 2003). The latter prefers to explicitly design large-scale modular cognitive architecture (Sandini, Metta & Vernon 2007), and the design choices often result from compromises between scientific and engineering criteria (Vernon, Metta & Sandini 2007). There are pros and cons to both approaches, but the modular engineering stance seems more closely related to the traditional computational theory of mind (Fodor 1983).

. There are other, related minimal approaches to the synthetic study of social interaction dynamics, including the behavior-based robotics approach by Dautenhahn and colleagues (e.g. Dautenhahn & Billard 1999) and going as far back as Grey Walter’s robotic ‘tortoises’. For the reasons mentioned at the start of Section 4.2, we prefer to focus on the minimal evolutionary robotics approach.

1. This intuition was grounded in a series of agent-based computer models of the nonlinear dynamics of turn-taking interactions (Ikegami & Iizuka 2007b, 2007a; Iizuka & Ikegami, 2004, 2003).

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Authors’ addresses

Tom Froese Shaun GallagherIkegami Laboratory (Building 16, Room 225b) Department of PhilosophyDepartment of General Systems Studies 327 Clement HallUniversity of Tokyo University of Memphis3-8-1 Komaba, Meguro-ku Memphis, TN 38152Tokyo 153-8902 USAJapan

[email protected]@gmail.com

Authors’ biography

Tom Froese received his D.Phil. in Cognitive Science from the University of Sussex (Brighton, England) at the beginning of 2010. The focus of his doctoral research was the interrelation-ship of life, mind and sociality, which he explored using a variety of approaches, including enactive theory, evolutionary robotics, and phenomenology. More recently, Froese has been interested in developing the methodological cross-section of phenomenological and dynami-cal system approaches in the science of consciousness. During 2010 he was a Postdoctoral Research Fellow at the Sackler Centre for Consciousness Science, also in Brighton. Currently,

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mailto:[email protected]

mailto:[email protected]



he is a JSPS Postdoctoral Research Fellow in the Ikegami Laboratory of the University of Tokyo, Japan, until the end of 2012.

Shaun Gallagher is an American philosopher. He currently holds the Moss Chair of Excellence in Philosophy at the University of Memphis, and is a Humboldt Foundation Anneliese Maier Research Fellow from 2012 to 2017. He has secondary appointments as Research Professor of Philosophy and Cognitive Science at the University of Hertfordshire, as Honorary Professor of Philosophy at the University of Copenhagen, and as Affiliated Research Faculty at the Institute of Simulation and Training at the University of Central Florida. He co-edits the journal Phenom-enology and the Cognitive Sciences. He is the author of several books, including How the Body Shapes the Mind (2005), Brainstorming (2008), Phenomenology (2012), and (with Dan Zahavi), The Phenomenological Mind (2012, 2nd ed.). He is also editor of The Oxford Handbook of the Self (2011).

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