Book contents
- The Cambridge Handbook of Computational Psychology
- The Cambridge Handbook of Computational Psychology
- Copyright page
- Contents
- Preface
- List of Contributors
- Part I Introduction
- Part II Cognitive Modeling Paradigms
- Part III Computational Modeling of Various Cognitive Functionalities and Domains
- 7 Computational Models of Episodic Memory
- 8 Computational Models of Semantic Memory
- 9 Models of Categorization
- 10 Micro-Process Models of Decision Making
- 11 Models of Inductive Reasoning
- 12 Mental Logic, Mental Models, and Simulations of Human Deductive Reasoning
- 13 Computational Models of Skill Acquisition
- 14 Computational Models of Implicit Learning
- 15 Computational Models of Attention and Cognitive Control
- 16 Computational Models of Developmental Psychology
- 17 Computational Models of Psycholinguistics
- 18 Computational Models in Personality and Social Psychology
- 19 Cognitive Social Simulation
- 20 Models of Scientific Explanation
- 21 Cognitive Modeling for Cognitive Engineering
- 22 Models of Animal Learning and Their Relations to Human Learning
- 23 Computational Modeling of Visual Information Processing
- 24 Models of Motor Control
- Part IV Concluding Remarks
- Author Index
- Subject Index
22 - Models of Animal Learning and Their Relations to Human Learning
from Part III - Computational Modeling of Various Cognitive Functionalities and Domains
Published online by Cambridge University Press: 05 June 2012
Edited by
Book contents
- The Cambridge Handbook of Computational Psychology
- The Cambridge Handbook of Computational Psychology
- Copyright page
- Contents
- Preface
- List of Contributors
- Part I Introduction
- Part II Cognitive Modeling Paradigms
- Part III Computational Modeling of Various Cognitive Functionalities and Domains
- 7 Computational Models of Episodic Memory
- 8 Computational Models of Semantic Memory
- 9 Models of Categorization
- 10 Micro-Process Models of Decision Making
- 11 Models of Inductive Reasoning
- 12 Mental Logic, Mental Models, and Simulations of Human Deductive Reasoning
- 13 Computational Models of Skill Acquisition
- 14 Computational Models of Implicit Learning
- 15 Computational Models of Attention and Cognitive Control
- 16 Computational Models of Developmental Psychology
- 17 Computational Models of Psycholinguistics
- 18 Computational Models in Personality and Social Psychology
- 19 Cognitive Social Simulation
- 20 Models of Scientific Explanation
- 21 Cognitive Modeling for Cognitive Engineering
- 22 Models of Animal Learning and Their Relations to Human Learning
- 23 Computational Modeling of Visual Information Processing
- 24 Models of Motor Control
- Part IV Concluding Remarks
- Author Index
- Subject Index
Summary
This chapter reviews a contingency learning against the background of recent formal models of animal learning. It reviews a very substantial amount of research including not only human causal and predictive learning but also category learning and multiple-cue probability learning. The development of theoretical models of predictive learning has been stimulated to an enormous extent by demonstrations that cues compete with each other to gain control over behavior (so-called cue interaction effects). In causal learning scenarios, the cue and outcome are provided, via the instructions, with particular causal roles. In most cases, then, the cues are not only potentially predictive of the outcome but also cause it. Despite the challenging nature of the evidence against an associative perspective as a unique account of human predictive learning, there is also evidence that the influence of causal knowledge or rule learning is not necessarily pervasive.
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- Information
- The Cambridge Handbook of Computational Psychology , pp. 589 - 611Publisher: Cambridge University PressPrint publication year: 2008
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- Cited by