Heuristics and Heuristics and Controlled Controlled Problem Problem SolvingSolving

“Forging the Link”

Forging the Link Forging the Link • How Motivation to Control interfaces with the

implicit and explicit cognitive processes that guide the organisms behavioral engagement of the ecology.

• How implicit cognitive processes are linked to Heuristics

• How explicit cognitive processes are linked to Controlled Problem Solving

MOTIVATION TO MOTIVATION TO CONTROLCONTROL

• The evolved function of the brain, cognitive, affective, and other systems is to attend to, process, and respond to the types of information that co-varied with survival or reproductive outcomes during the species evolutionary history.

• Combinations of these systems as they are linked to behavioral engagement of the environment represent a functional model.

• Purpose of evolved behaviors is to recreate outcomes that facilitated survival or reproduction

• Implicit cognitive Implicit cognitive process which are process which are features of the modular features of the modular systems that guided systems that guided behavioral engagement behavioral engagement of the environment .of the environment .

Explicit cognitive Explicit cognitive

processes that support processes that support

problem solving about problem solving about

potentially important potentially important

outcomes or relations outcomes or relations

in the environmentin the environment.

Cost Benefit Cost Benefit Trade-Offs Trade-Offs

Characteristics of Implicit and Explicit Cognitive Systems

Implicit System Explicit System

Unconscious Conscious

Automatic Controllable

Evolved Early Evolved Late

Common across species Might be unique to humans

Pragmatic, context – dependent expression

Logical, decontextualized abstract representations

Parallel processing of multiple sources of contextual information ( e.g. face, body posture, vocal intonation)

Sequential processing of decontextualized abstract representations

Parallel processing results in high but effortless information-processing capacity

Sequential processing is limited by attentional and working memory resources and is therefore effortful

Unrelated to general intelligence

Correlated with general intelligence

• Most basic trade off Most basic trade off involves balancing the involves balancing the speed of behaviorally speed of behaviorally responding to the responding to the ecology against the ecology against the accuracy of identifying accuracy of identifying ecological informationecological information

• These brain and These brain and cognitive systems are cognitive systems are likely to evolve to likely to evolve to capture information capture information that has been reliably that has been reliably associated with associated with survival or survival or reproductive outcomes reproductive outcomes in evolutionary history. in evolutionary history.

he

Heuristics: Fast, Frugal, simple, and implicit mechanisms

Controlled Problem -Solving: Slow, effortful, complex, and explicit/conscious mechanisms

Invariant

VariantInformation Patterns

Variance- Variance- InvarianceInvariance

• The evolution of implicit and explicit cognitive systems can be tied to directly to evolutionarily significant information patterns that have tended toward the invariant and variant ends of the continuum

Bounded RationalityBounded Rationality• Simon(1955,1956) argued

that behaviors, cognitions, and brain functions are fully understandable only when placed in the type of ecological context that drove their evolution,

• Relation between exoskeleton systems and information in the ecology

• Timberlake (1994) argues the relation can be understood in terms of Pavlovian conditioning.

• There is a relation between the here-and-now mechanisms that guide behavioral decision making and the ecologies in which these mechanism have evolved.

Satisficing and Satisficing and Aspiration levelAspiration level

• Cognitive mechanisms that support decision making and behavioral engagement are not considered to be optimal

• Combined cost of limited ecological information, limited cognitive resources and delayed behavioral responding to the ecology make the evolution of the brain and cognitive systems that optimize unlikely

• Evolution favors Satisficing and Aspiration level

• Satisficing- motivational and behavioral systems will be directed toward achieving an ecological goal that satisfies a basic need. Results in outcome that is “good enough”

• Aspiration level- organism my continually adjust the definition of what is “good enough” on the basis of most immediate success and failure

Megalomania

Mate ChoiceMate Choice

• Pairs of Barnacle Geese bond for many breeding seasons and choose mates according to size and age

• Creates conditions that will favor the evolution of brain, cognitive, and behavioral mechanisms that will guide mate choice decisions

• Black et al. (1996) found that individuals that sampled potential mates and switched mates if a marginally better one was found had 50% reduction in the probability of successfully breeding during the season.

• Cost of mate switching and comparing potential mates on one or more dimensions place serious limits on the potential for the evolution of socially and cognitively sophisticated optimizing mechanisms

Barnacle Geese

HeuristicsHeuristics• They often lead to

near optimal decision making in many real world situations, that is, the type of situations in which these decision making mechanisms likely evolved.

• When a bounded rationality match between internal systems and ecological conditions is achieved heuristic-based decisions and behavioral responses are executed.

• The combination of mechanisms that enable information to be identified and processed quickly and that enable fast and frugal decision making

• Decision making rules of thumb

• Tversky and Kahneman et. (1974,19820)

• Availability heuristics- people tend to judge things or make inferences about the likely hood of a situation occurring based on how easily they can recall the occurrence from long term memory

Complex Social Complex Social DynamicsDynamics

• Comides(1989) - Humans have evolved heuristics that guide reciprocal social exchanges.

• Brosnan and de Waal(2003)- demonstrated that capuchin monkeys have a sense of fair play

• Comides, Tooby, and Knight (2002)-areas of the Prefrontal neocortex (theory of the mind) and the amygdala (affect-eliciting social information) are the neural systems behind our “fairness” heuristic

Anterior cingulate

Cortex

Dorsolateral prefrontal

cortex

Controlled Problem Controlled Problem SolvingSolving

• Effortful processing that is most evident in conditions that deviate from expectations

• Variant, explicit in nature, abstract

• Knowledge lean domains –little prior knowledge or exposure to problem or situation

• Operators- rules that define how people can change the initial state into the successive intermediate states that ultimately lead to the desired goal.

• Problem Space- defined by state representations

• Goal of problem solving is to change the initial state to the desired end state

Knowledge –Knowledge –Lean DomainsLean Domains

Newell and Simon (1972) Newell and Simon (1972)

discovered that common discovered that common

approach to solving similar approach to solving similar

problems involves a means-problems involves a means-

end analysisend analysis

1.Current state compared to 1.Current state compared to

desired end statedesired end state

2. Memory is searched to 2. Memory is searched to

identify operations that can be identify operations that can be

used to reduce the difference used to reduce the difference

3. Operation chosen, executed 3. Operation chosen, executed

and resulting state compared and resulting state compared

to desired stateto desired state

Initial State

End State

Container 3 3 ounces

Container 2 5 ounces

Container 1 8 ounces

Means-End Means-End AnalysisAnalysis

• With experience

solving a

particular type of

problem , people

can develop

heuristics that

simplify movement

through problem

space.

• These learned

heuristics are

formed during a

individuals life

time

Knowledge-Knowledge-Rich DomainsRich Domains

• Most problem solving in the real world occurs for domains in which individuals have varying degrees of experience knowledge

• Ill structured

• Influenced by nature and extent of the individual’s declarative knowledge

• Schemata –memory systems of linked operations and the sequence in which they were executed in previous problem-solving.

Goal Definition

Reasoning: Analogy, Induction, Deduction

Assumptions Constrain Problem

Space

Goal Relevant Knowledg

e

Legal Operato

rs

Schemata

Problem Representati

on and Transformatio

n

General Problem Solving

Strategies

Reasoning and Reasoning and Mental ModelsMental Models

• Ability to engage in rational analysis and reason through difficult problems captures aspects of general intelligence.

• Have the ability to mentally generate, maintain and manipulate abstract representations but it is limited by limitations in attentional and working memory resources.

• Mental models - pattern of representations used as an analog simulation of a specific situation or state of affairs in the world.

• Constructed through language or images.

• Proposition- the important language component , most basic unit of meaning.

• Images- can be vivid and perceptual-like or composed of nonvisual spatial representations.

Inhibition Inhibition

• Most people’s decision making and inference drawing often results from bounded rationality and heurists as well as acquired tasks-relevant knowledge

• John- Laird (1983) argued that in most situations , people’s reasoning is based not on the formal rules of logic, but rather on the construction of a mental model of the information presented.

• Most humans have the crucial ability to inhibit heuristic –based responses and draw inferences on the basis of explicit processes

• The ability to modify heuristics-based processes is most likely to evolve in situations in which two species are in competition or with intense social competition.

Syllogism

•All people taller than

6ft 5in are basketball

players

•Joe is 6ft 7inch tall

•Therefore, Joe is a

basketball player

•What conclusion

would you draw?