Intelligent Learning Devices in Planning Dino Borri Technical University of Bari Via Orabona 4, 70125 Bari Tel. +39 080 5963347, E-Mail: [email protected]

Intelligent Learning Devicesin Planning

Dino BorriTechnical University of BariVia Orabona 4, 70125 Bari

Tel. +39 080 5963347, E-Mail: [email protected]

Computation Models in Design and Planning Support

September 7, 2002 – UCL CASA, London

Intelligent Learning Devices in Planning

Dino Borri - Politecnico di Bari 2

Summary• Introduction• Intelligence• Planning• Intelligence and Planning• Exploration and Creativity• Memory, Intelligence and Creativity• Exploration, Intelligent Plans and Computers• Role of memory• Scenario Building: Mediterranean Experience• Conclusions



Introduction

Strong limits of classical planning in Socio-Environmental Domain.

Need in SED for massive use of case-based reasoning and memories.

New architectures for memory management.

Integration between less structured and more interactive representations of futures and plans.

Emergence of creativity from diversity and interaction.

Need for more experimentation of the new interactive planning environments in the perspective of intelligence.



Intelligence

Traditionally is considered intelligent a person who:

• reasons in relation to different situations, that is in a contextualized way, but also, when necessary, independently from those situations

• reasons in a way at the same time ‘normal’ and original

• reasons in a way rich of sensorial and at the same time symbolic interactions



• reflects in action (self criticism, rethinking, continuous learning, concern for external reality, irony towards him/herself, etc.)

• solves problems not easy for others

• is well informed and rich in memory but at the same time is able to think and act free form these charges

• etc.



It is well known in IT the multi-stage, evolutionary, model of cognition, from data to information, to knowledge, to intelligence.

Some pitfalls:• transition from one level to the other• mono-directionality or bi-directionality?• how to classify different forms of intelligence? (wisdomness, creativity, knowledgeability, etc.)

Probably better:• use of less rigid and less evolutionary model• agents can be different in different situations



How to judge intelligence?

• Not resorting to formal education and training

• Merging substance and procedure

• Evaluating its development in a context: intentional and/or occasional opportunities

• Evolution and maturation with time: exposure to social life and linguistic interaction (problematic case is the development in isolation), widening of psyco/physical experiences and memories, etc.



• Presence of common sense, experiential, multicriteria judgements

• Critiques to deterministic tests (see IQ) as they do not account for contexts, contradictions, etc.

• Avoiding to assume the judgement on intelligence as completely different from other judgements: on psycho-physical features of persons; judgement on intelligence can be arbitrary as others

Reasoning on intelligence cannot be robust: it is always partial, biased evaluation and representation



Planning

In the domain of socio-environmental phenomena and its policies, the argumentative and communicative approach to planning and plans is increasingly a substitute for the traditional cybernetic approach based on the linear control, by elements and phases, of systems dynamics (Forester, 1989, 1999; Healey, 1997, 2002). A weak and contextual rationality, multilogic and multivalue, substitutes a strong and absolute rationality (Borri, 2002).



A set of contingent architectures, to build almost as in a bricolage, to challenge ill-(or non-)structured situations and dynamics, substitutes a formal and well-structured means-ends architecture of the plan, made of phases and operations allowing the transition from a system’s ‘state’ to another and in particular from the system’s ‘initial’ state to the system’s ‘final’ (goal) state.

More than aiming at goal achieving, the new plans aim at building discourses and visions related to evolving situations functioning as backcloths where different actors, institutional and non-institutional, collective and individual, can intentionally locate their behaviours in agreement or conflict learning at the same time about themselves and the realities in which they are immersed.



A notion of immersion substitutes the one of direction (Sardar, 2002).

If what is going on is a strategic approach to planning, interested in those specific transitions between states which materialize the chaotic and probabilistic game of the new interactive plans, what is emerging is also a visionary approach linked to trusts and beliefs: in this, futures belong to heart more than mind, so that we are no long interested in the rational motivations and details of building up them as they appear to us as given by gift or chance or conquered via transformative practices too impetuous to let decisions and actions, the typical articulations of a plan in the cybernetic and control engineering tradition, be clearly detectable from outside.



To these new plans a number of institutional/non-institutional, individual/collective, expert/ingenuous actors bring visions and beliefs of possible, feared, or desired things whose happenings and evolutions can be preferably avoid or facilitate by resorting to a recipes book of stories which were lived or learned by tale, represented in synthetic form or in the deformation caused by drawing to memory and tale, in the indifference for the sometimes distant times and places of references, for the constructive details.

Only in a subsequent time more detailed planning and design frames will be offered to discussion, rarely, according to the circumstances: these more detailed frames will be more concerned with the provision of definite representations and solutions, with phases, decisions, specific actions taken as alternative, resources and constraints in detail etc.



Perhaps we are not speaking about a completely new planning. Is it true or not, in fact, that since planning as modern organizational technique for representing and/or solving complex and strategic problems for individuals and groups per se exists never we found clarity in it about goals and actions, times, resources, convergences, conflicts, as there was a preference for setting environments of possibilities and discourses for games that in the end were the ones that are typical in power and politics.



The theoretical and practical limitations of the systems and strong rationality approach, based on the linearity of trajectories of elements and states, when applied to the probabilistic and chaotic –instead than deterministic- phenomena of the socio-environmental domain where it is extremely hard to point out elements, to schedule times, to respect coherences. In these phenomena, in fact, information about state conditions is never complete, a plurality of intentions and beliefs and related -generally conflicting- actions has to find almost impossible convergences: difficulties which are added to the well known computational asperity of the systems approach, due to the ‘combinatorial explosion’ of the possible trajectories activated by the enormous number of decisions to be taken at the knots of the ‘decision trees’ of those trajectories.



Moreover, a part from the desires of the literature on planning implementation which flourished in 1980s and 1990s, we must admit that in the socio-enviromental domain practical cases of experimentation of this kind of planning and plans are extremely rare, even if we consider sporadic explicit theoretical claims and models. So it his hard to give sufficient scientific trust to our discussion about the actual attitudes and potentials of such planning and plans in those domains.



The argumentative and communicative approach has a character more incremental and adaptive, develops a theory-(reflection-)in-action, in as much initially, theoretically speaking, only a problematic reference frame, about situations and tendencies and of knowledge (now increasingly hybrid: expert and common) relating to them and the possibility of influencing them, is given.

Planning and plans become processes of problem setting (more than problem solving), of individual and collective learning about situations as well as ‘problems’, towards futures appearing now as problematic, in part given and in part construed, never analysable if not in the form of possibility horizons (Schön, 1983; Schön and Rein, 1996, Puglisi, 1999).



It is not useful, perhaps, to emphasize the substantial difference between this second and more recent contextual and multivalue logic approach to planning and plans, because of the inherent plurality of the involved actors and the consideration of contexts and their evolutionary and chaotic dynamics, and the first one, ruled by a formal logic and synoptic and anticipative rationality unfortunately systematically defeated by unpredictables and insurgences.



Experimentations of the argumentative and communicative approach, even if two decades younger than the other, appear more diffuse and consistent: the collective and explicit, argumentative, character of the ‘debates’ or ‘discourses’ of planning and plans, the need of building in explicit way backcloths and arenas for the interaction of people who must, can or want to be stakeholders in it, are all conditions of a greater transparency of the process. In this way, the implementation too can be better analysed and valued, as it already happens for many of these experiences, in a currently enormous set whose enlargement is fuelled by the emergent dramatic socio-environmental issues of the planet Earth.



The two approaches are not completely separated, however, in as much for instance meaningful elements of the classical rational model consciously or unconsciously continue to animate the behaviours of individual actors in the new interaction game and to shape the basis on which convergences and conflicts develop (Borri, 2002).

What is probably worth to note here is the peculiar perspective angle which is given to the theory and practice of planning and plans by the spreading of ‘intelligent’ computerised procedures, in environments of ‘artificial intelligence’.



In this context classical planning since long has dominated, in a domain of generally (logic-)mathematic or mechanic-deterministic problems, and only in the last period heuristics and ‘multiagencies’ (and related multivalue logics) and the refinement and complexity increasing (for instance for the increased plurality) of intelligences have introduced the problem of planning and plans in terms more adequate to what is demanded by the ill-structured character of the socio-environmental domain so dear to scholars and professionals as we are.



More, the very features assumed, in the above mentioned domain, by the argumentative and communicative planning, with its ‘speech acts’ organized in form of ‘protocols’, its ‘stories’ and individual and collective ‘biographies’, and convergences and conflicts of its interactions, its games and strategies, its learning procedures, its qualitative and quantitative descriptions and representations, and whatever else today denote this type of quite successful planning, provide some suggestive indications for the operational arise of the levels of intelligence attained by artificial setters and solvers of ‘problems’.



According to McDermott (1999), the point of ‘classical planning’ is “to generate a sequence of actions which makes a proposition true, in a domain in which perfect information exists about the initial state of the world and the effects of every action”.

This classical type of planning and plans is forced to make use of a ‘search’, in the space of all the possible actions and the related sequences, by the ‘intractability’ of all its target problems which could embody a real interest and avoid triviality. An exploratory search, where the value of the heuristic is increasingly appreciated, to avoid the combinatorial explosion of the possible paths in the exploration space.



According to McDermott, the ‘states of the world’ (‘situations’) are described in form of sets of ‘atomic’ propositions while ‘actions’ are described using PDDL (Planning Domain Definition Language) (Mc Dermott, 1998), an evolution of ADL (Action Description Language) developed by Pednault at the end of 1980s to integrate Strips-like notions (developed for problem solving and theorem proving by Fikes and Nilsson in the early 1970s and still largely used, in particular for treating propositions while they fit less to numbers and geometries) and situational calculus.



Intelligence and planning

In an expert vision, a plan is an organized set of transitions, real or virtual, from a state to another of the world;it is a complex/organized, anticipative/reactive reflection or action finalised to represent or solve a complex problems.

Plans are prepared, in general, when collective responsibilities are involved, but even strategic personal problems can ask for a plan; in facts plans appear when we want them to appear…



Plans are sets of decisions: they live in continuous space while decisions live in discrete space.

We assume intelligent planning as mobilization of intelligences for a task (even without a predefined goal) with an approach being non-deterministic, exploratory, open to cognitive emergences (other agents appear…) and to changes-in-action in task implementation because of self-consciousness.

Individuals who make plans can be seen as intelligent or not, pleasant or not according to the circumstances; organizations who make plan are more frequently associated to intelligent behaviour.

Classical intelligent planning does not appear able to compete with organizations and multiagencies.



Individual and/or organizational intelligence

Many contradictions in current literature on organizational development and social learning as regards to intelligence.

Individual intelligence continues to be central in the scene and intelligent organizations are defined by their attitude to facilitate transfers and interactions of individual intelligences.

But a more complex social perspective is appearing: see system thinking, organizational learning, etc.



In argumentative and communicative planning (Forester) where new visions and solutions can emerge, organization is seen as creative intelligence.

In single agents cognitive performances are more routinary and based on case memory.

How to evaluate learning and cognitive performances in organizations?

• Individual skills vs collective performances

• Intellectual vs manual work



Experimentations are missing. In literature a dominant position denies the emergence of new and creative properties in collective intelligences where resistances to integration and composition of differences and individual positions affirmations are observed.

In strategic and interactive planning many experiences show knowledge and plans generation in discourse and political communities. Are there shared criteria to evaluate these cognitive processes?



Socio-environmental domain and plansIn Socio-Environmental Domain (SED) intelligent plans do not exist:

• current classical planning is far from being able to deal with the complexity deriving from the interactive, political, evolutive, institutional and collective nature of socio-environmental planning

• only partial plans can be considered useful and possible, as peaces of technical rationality to support human actions and thoughts

• current intelligent plan in SED can intervene only after an agreement, even transitory, on action has been reached reducing the complexity of search space



Exploration and creativityWhat does ‘creativity’ mean?

Creativity can be considered a process of transformation, of re-combination of what was already existing in a different form.

In a social perspective, when a person or an organization can be considered creative?

Usually we consider creativity an innate ability which is manifested “outside the norms” through original creations which are origins, starts of something not existing before.

Can a scientist be considered creative in the same sense of an artist?



In composition creativity is an original start of a transformation which will proceed according to an order, a sequence, almost musical …

Are intelligence and creativity related or in opposition? Is creativity related to specialization, to reasoning and acting in a specific domain. Is intelligence related to generalizations, independently from a specific domain?

But intelligence and creativity are related to the ability of abstracting from contexts and realities …

Intelligence appears more comprehensive than creativity; thus creative intelligence would be the highest level of intelligence …



How does creativity emerge?

Some great creative artists learnt from other creative artists …

Does creativity emerge within complex and organized societies? Power can play a role in defining the quality of creativity and affect the judgement of creativity …

Museums are extraordinary places of memory and social conventions reflecting main tastes.

Creativity is reduction of complexity, simplicity emerging from complexity and allows to look at complexity from a detached and not conventional point of view.



Do complex systems enable creative behaviours?

Biodiverse systems can more easily produce new transformations than a simple system. Creativity, as any other transformation, uses the plurality and the numerousness of the elements from which it arises. Even openness of each biodiverse system to the others is a condition for transformations.



The higher is the number of possible combinations of elements the higher is the probability for new, creative transformations to emerge.

Creativity has a probabilistic nature and is associated to great numbers (of people and resources): the more are people committed in transformation the more probable is that creative people emerge among them

Creating means exploring and building the new.

We need new ontology.



Memory, intelligence and creativity

Variety is at the same time live and memory of variety: living systems and associated memories are fundamental blocks of life.

Deep and shallow memories exist. They stratify in some way as in a store, not in a positional, topological framework but as configurations, neuronal schemes.

Memories can be accessed through keys which are ‘positional’, multiple indexed (temporal, situational, linguistic, associative, etc.). These keys enable different forms of recovering even when some indexes are lost.



Intelligent and creative people have great and durable memory stores and use them to look for schemes for problem solving, for old and new organizations, small blocks for original transformations and re-combinations …

Intelligent people produce numerous indexes because of their associative reasoning ability.

What is the relationship between memory and creativity? Creativity is about a peculiar attitude towards a non conventional transformation of reality which is represented in form of memory. It depends on contexts, environments, masters, points of references, and life choices.



Exploration, Intelligent Plans and Computers

Memory is a basic component of reasoning and intelligence. Thus computers are seen as relevant supports to reasoning tasks.

Reasoning is at the same time substantive (memory) and procedural (elaboration for transformation); procedure is an explorative and reactive association in a sensorial interaction with reality.



To produce an intelligent plan, a machine needs to combine control with reactive adaptation abilities which are possible only when sensorial skills are given and experience is consciously acquired.

Such a behaviour is hard in a machine because it is neither a living system or able to make autonomous decisions: the machine would need to consider all the possible cases in a search space which is infinite.

This introduces the problem of heuristics able to guide the search.



Role of memory

The architecture of memory is not well known. Memory can be divided into deep memory and operative memory (Anderson): the operative one allows to access the deep. May be they are two different representations of the same store: the first is partial, synthetic but essential, the second is complete.

In the memory store, representations, similarly to indexes, are multiple: memories of events and experiences are stored in disaggregated (elementary small block with relevant links) and aggregated forms (classes of events-experiences).

The disaggregated form makes easier implementations, controls and revisions; the aggregated one addresses general comparisons, orientations, choices and decisions, and in general the immediate reactive reasoning.



A planner often behaves according to the following scheme:

• he/she interactively represents the planning problem;

• enters the store of case memories to find there proper cases of solutions or of probable evolution in the future; details are delayed;

• goes to interactive planning meeting with some predefined ideas on possible solutions and/or futures;

• shows availability to retrieve new case memories for the problem at hand and most of all to add new memories to his/her store only when the planning story at hand appears significantly developed and assessable.



In interactive and communicative planning, due to the more relevant agents’ need of reviewing theories as memory representations, the ‘theory in action’ mechanism, that is a strong continuous link between reasoning and action, is crucial.

This kind of planning must be more action-oriented than the traditional one because action and its evaluation is fundamental condition of a wide and significant memory mobilization.



Scenario Building: Mediterranean Experience(http://www.iamb.it/incosusw)

Concerted Action, EU funds (1998‑2003).

Goal: enabling the construction of sustainable politics in the mediterranean area by partecipative scenario building.

Phases:

–Tunis 2000: agricolture/urbanization,–Izmir 2001: coasts integrated management,–Rabat 2002: local/global dimensions and mediterranean

commerce.

Computer assisted scenario building.



1. Back-viewmirror analysis

2. Futures exploration

3. Identification of obstacles

4. Ident. of

policies

5. Ident. of

resources

6. Aggregation into scenarios

Group 1 Group 2 Group 3

Grouping similar scenarios

Alternative scenario 1






4.Identif.of policies

5.Identif.of resources





4.Identif.of policies

5.Identif.of resources




Step 1 - Listing structural changes occurred in the past

Step 3 – Rating grouped issues

Rated list

rate rate rate rate rate rate rate rate

Ranked list

Is there agreementon the ranked list?

Final shared list of changes occurred in the past

Step 4 – Selecting and ranking top 10 issues in the list

Step 2 - Grouping similar and/or redundant issues under synthetic headings

Step 5 - Dropping off the least ranked issues

Step 6 - Free discussion on the outcomes of the ranking (‘chat’)

YES

NO

St.7 - ResumeDelphi Tour

St.5a -Self-rankinglevel of knowledge

St.6a -Self-rankinglevel of knowledge

1 2 3 4 5 6 ... n

list list list list list list list list

rank rank rank rank rank rank rank rank

1 2 3 4 5 6 ... n

Generated list of changes

1 2 3 4 5 6 ... n

St.3a -Extracting listwith single ratings

St.4a -Extract listwith single ratings

IT support

Goals: managing and improving Delphi processes through questionnaires in order to build a convergence in focusing problematic issues

Software: MeetingWorks©, a LAN system with a coordination station (chauffeur) and peripherical stations for participants.



Rabat agenda



starting representation

….Ag. 1 Ag. 2 Ag. 3 Ag. i

action 1 (set of actions…)

partial plan 1A

partial plan 1B

not planned action….

shared (collective) representation 1

Ag. 1 Ag. 2 Ag. 3 Ag. i….

… towards representation and action n

plan development with no new agent irruption


partial plan 2A

partial plan 2B





plan development with new agents irruption

new agents need to work on the starting representation and on representation/actions 1 before representation and action 2 are developed

starting representation

….Ag. 1 Ag. 2 Ag. 3 Ag. i

Ag. 1 Ag. 2 Ag. 3

Ag. m...

… towards representation / action 2 and…n

Ag. i+1...


partial plan 1A

partial plan 1B





Conclusions

Classical planning not usable in SED.

Only partial plans in the classical tradition can be used but in the de-structured, interactive environments of the new argumentative, communicative planning approach but with a further condition: that an agreement on action has been reached.

Large numbers of cognitive agents involved guarantee significant mobilizations of memories and related representations of the world (i.e. theories…) and hence more probable emergence of creative representations of the world.

Documents

Intelligent Learning Devices in Planning Dino Borri Technical University of Bari Via Orabona 4, 70125 Bari Tel. +39 080 5963347, E-Mail: [email protected]