The Soft Constraints Hypothesis: A Rational Analysis Approach to Resource Allocation for Interactive Behavior

Soft constraints hypothesis (SCH) is a rational analysis approach that holds that the mixture of perceptual-motor and cognitive resources allocated for interactive behavior is adjusted based on temporal cost-benefit tradeoffs. Alternative approaches maintain that cognitive resources are in some sens...

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Bibliographic Details
Published in:Psychological review 2006-07, Vol.113 (3), p.461-482
Main Authors: Gray, Wayne D, Sims, Chris R, Fu, Wai-Tat, Schoelles, Michael J
Format: Article
Language:English
Subjects:
Analysis
Behavior
Behavioural psychology
Biological and medical sciences
Cognition
Cognitive Processes
Cognitive style
Comparative Analysis
Cost-benefit analysis
Developmental psychology
Experimental Psychology
Fundamental and applied biological sciences. Psychology
Human
Human Computer Interaction
Humans
Hypotheses
Hypothesis Testing
Interactive learning
Interpersonal Relations
Learning
Learning. Memory
Memory
Models, Psychological
Perceptual Motor Coordination
Perceptual Motor Processes
Problem Solving
Psychological Theory
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Rationality
Reinforcement
Reinforcement (Psychology)
Resource Allocation
Social Behavior
Social psychology
Statistical Analysis
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Summary:Soft constraints hypothesis (SCH) is a rational analysis approach that holds that the mixture of perceptual-motor and cognitive resources allocated for interactive behavior is adjusted based on temporal cost-benefit tradeoffs. Alternative approaches maintain that cognitive resources are in some sense protected or conserved in that greater amounts of perceptual-motor effort will be expended to conserve lesser amounts of cognitive effort. One alternative, the minimum memory hypothesis (MMH), holds that people favor strategies that minimize the use of memory. SCH is compared with MMH across 3 experiments and with predictions of an Ideal Performer Model that uses ACT-R's memory system in a reinforcement learning approach that maximizes expected utility by minimizing time. Model and data support the SCH view of resource allocation; at the under 1000-ms level of analysis, mixtures of cognitive and perceptual-motor resources are adjusted based on their cost-benefit tradeoffs for interactive behavior.
ISSN:0033-295X
1939-1471
DOI:10.1037/0033-295X.113.3.461