Ron Sun

Anatomy of the Mind

Exploring Psychological Mechanisms and Processes with the Clarion Cognitive Architecture

• Gebundenes Buch

Produktbeschreibung

This book aims to understand human cognition and psychology through a comprehensive computational theory of the mind, namely, a "cognitive architecture."

Produktdetails

• Verlag: Oxford University Press, USA
• Seitenzahl: 480
• Erscheinungstermin: 18. Mai 2016
• Englisch
• Abmessung: 236mm x 155mm x 30mm
• Gewicht: 816g
• ISBN-13: 9780199794553
• ISBN-10: 0199794553
• Artikelnr.: 47866760

Autorenporträt

Dr. Ron Sun is Professor of Cognitive Sciences at Rensselaer Polytechnic Institute. A well-known cognitive scientist, Ron Sun explores the fundamental structures of the human mind. He aims for the synthesis of many intellectual ideas into a coherent model of the human mind. The goal is to come up with a cognitive architecture that captures a variety of psychological processes and provides unified explanations of a wide range of data and phenomena.

Inhaltsangabe

* Table of Contents
* Preface
* Chapter 1. What is A Cognitive Architecture?
* 1.1. A Theory of the Mind and Beyond
* 1.2. Why Computational Models/Theories?
* 1.3. Questions about Computational Models/Theories
* 1.4. Why a Computational Cognitive Architecture?
* 1.5. Why CLARION?
* 1.6. Why This Book?
* 1.7. A few Fundamental Issues
* 1.7.1. Ecological-Functional Perspective
* 1.7.2. Modularity
* 1.7.3. Multiplicity of Representation
* 1.7.4. Dynamic Interaction
* 1.8. Concluding Remarks
* Chapter 2. Essential Structures of the Mind
* 2.1. Essential Desiderata
* 2.2. An Illustration of the Desiderata
* 2.3. Justifying the Desiderata
* 2.3.1. Implicit-Explicit Dichotomy and Synergistic Interaction
* 2.3.2. Separation of the Implicit-Explicit and the
Procedural-Declarative Distinction
* 2.3.3. Bottom-up and Top-down Learning
* 2.3.4. Motivational and Metacognitive Control
* 2.4. Four Subsystems of CLARION
* 2.4.1. Overview of the Subsystems
* 2.4.2. The Action-Centered Subsystem
* 2.4.3. The Non-Action-Centered Subsystem
* 2.4.4. The Motivational Subsystem
* 2.4.5. The Metacognitive Subsystem
* 2.4.6. Parameters of the Subsystems
* 2.5. Accounting for Synergy within the Subsystems of CLARION
* 2.5.1. Accounting for Synergy within the ACS
* 2.5.2. Accounting for Synergy within the NACS
* 2.6. Concluding Remarks
* Chapter 3. Subsystems, Modules, and Algorithms I: The Action-Centered
and Non-Action-Centered Subsystems
* 3.1. The Action-Centered Subsystem
* 3.1.1. Background
* 3.1.2. Representation
* 3.1.2.1. Representation in the Top Level
* 3.1.2.2. Representation in the Bottom Level
* 3.1.2.3. Action Decision Making
* 3.1.3. Learning
* 3.1.3.1. Learning in the Bottom Level
* 3.1.3.2. Learning in the Top Level
* 3.1.4. Level Integration
* 3.1.5. An Example
* 3.2. The Non-Action-Centered Subsystem
* 3.2.1. Background
* 3.2.2. Representation
* 3.2.2.1. Overall Algorithm
* 3.2.2.2. Representation in the Top Level
* 3.2.2.3. Representation in the Bottom Level
* 3.2.2.4. Representation of Hierarchies
* 3.2.3. Learning
* 3.2.3.1. Learning in the Bottom Level
* 3.2.3.2. Learning in the Top Level
* 3.2.4. Memory retrieval
* 3.2.5. An Example
* 3.3. Knowledge Extraction, Assimilation, and Transfer
* 3.3.1. Background
* 3.3.2. Bottom-Up Learning in the ACS
* 3.3.2.1. Rule Extraction and Refinement
* 3.3.2.2. Independent Rule Learning
* 3.3.2.3. Implications of Bottom-up Learning
* 3.3.3. Top-down Learning and Assimilation in the ACS
* 3.3.4. Transfer of Knowledge from the ACS to the NACS
* 3.3.5. Knowledge Extraction in the NACS
* 3.3.6. Transfer of Knowledge from the NACS to the ACS
* 3.3.7. An Example
* 3.3.7.1. Learning about "Knife "
* 3.3.7.2. Learning about "Knife " within CLARION
* 3.3.7.3. Learning More Complex Concepts in CLARION
* 3.4. General Discussion
* 3.4.1. More on the Two Levels
* 3.4.2. More on the Two Learning Directions
* 3.4.3. Controversies
* 3.4.4. Summary
* Appendix
* A.1. Response Time
* A.1.1. Response Time of the ACS
* A.1.2. Response Time of the NACS
* A.2. Learning in MLP (Backpropagation) Networks
* A.3. Learning in Auto-associative Networks
* A.4. Representation of Conceptual Hierarchies
* Chapter 4. Subsystems, Levels, and Algorithms II: The Motivational
and Metacognitive Subsystems
* 4.1. Introduction
* 4.2. The Motivational Subsystem
* 4.2.1. Essential Considerations
* 4.2.2. Drives
* 4.2.2.1. Primary Drives
* 4.2.2.2. Secondary Drives
* 4.2.2.3. Approach versus Avoidance Drives
* 4.2.2.4. Drive Strength
* 4.2.3. Goals
* 4.2.4. Modules and Their Functions
* 4.2.4.1. Initialization Module
* 4.2.4.2. Preprocessing Module
* 4.2.4.3. Drive Core Module
* 4.2.4.4. Deficit Change Module
* 4.3. The Metacognitive Subsystem
* 4.3.1. Essential Considerations
* 4.3.2. Modules and Their Functions
* 4.3.2.1. Goal Module
* 4.3.2.2. Reinforcement Module
* 4.3.2.3. Processing Mode Module
* 4.3.2.4. Input/output Filtering Modules
* 4.3.2.5. Reasoning/learning Selection Modules
* 4.3.2.6. Monitoring Buffer
* 4.3.2.7. Other MCS Modules
* 4.4. General Discussion
* 4.4.1. Reactivity versus Motivational Control
* 4.4.2. Scope of the MCS
* 4.4.3. Need for the MCS
* 4.4.4. Information Flows Involving the MS and the MCS
* 4.4.5. Concluding Remarks
* Appendix: Additional Details of the MS and the MCS
* A.1. Change of Drive Deficits
* A.2. Determining Avoidance versus Approach Drives, Goals, and
Behaviors
* A.3. Learning in the MS
* A.4. Learning in the MCS
* A.4.1. Learning Drive-Goal Connections
* A.4.2. Learning New Goals
* Chapter 5. Simulating Procedural and Declarative Processes
* 5.1. Modeling the Dynamic Process Control Task
* 5.1.1. Background
* 5.1.2. Task and Data
* 5.1.3. Simulation Setup
* 5.1.4. Simulation Results
* 5.1.5. Discussion
* 5.2. Modeling the Alphabetic Arithmetic Task
* 5.2.1. Background
* 5.2.2. Task and Data
* 5.2.3. Top-down Simulation
* 5.2.3.1. Simulation Setup
* 5.2.3.2. Simulation Results
* 5.2.4. Alternative Simulations
* 5.2.5. Discussion
* 5.3. Modeling the Categorical Inference Task
* 5.3.1. Background
* 5.3.2. Task and Data
* 5.3.3. Simulation Setup
* 5.3.4. Simulation Results
* 5.3.5. Discussion
* 5.4. Modeling Intuition in the Discovery Task
* 5.4.1. Background
* 5.4.2. Task and Data
* 5.4.3. Simulation Setup
* 5.4.4. Simulation Results
* 5.4.5. Discussion
* 5.5. Capturing Psychological "Laws "
* 5.5.1. Uncertain Deductive Reasoning
* 5.5.1.1. Uncertain Information
* 5.5.1.2. Incomplete Information
* 5.5.1.3. Similarity
* 5.5.1.4. Inheritance
* 5.5.1.5. Cancellation of Inheritance
* 5.5.1.6. Mixed Rules and Similarities
* 5.5.2. Reasoning with Heuristics
* 5.5.2.1. Representativeness Heuristic
* 5.5.2.2. Availability Heuristic
* 5.5.2.3. Probability Matching
* 5.5.3. Inductive Reasoning
* 5.5.3.1. Similarity between the Premise and the Conclusion
* 5.5.3.2. Multiple Premises
* 5.5.3.3. Functional Attributes
* 5.5.4. Other Psychological "Laws "
* 5.5.5. Discussion of Psychological "Laws "
* 5.6. General Discussion
* Chapter 6. Motivational and Metacognitive Simulations
* 6.1. Modeling Metacognitive Judgment
* 6.1.1. Background
* 6.1.2. Task and Data
* 6.1.3. Simulation Setup
* 6.1.4. Simulation Results
* 6.1.5. Discussion
* 6.2. Modeling Metacognitive Inference
* 6.2.1. Task and Data
* 6.2.2. Simulation Setup
* 6.2.3. Simulation Results
* 6.2.4. Discussion
* 6.3. Modeling Motivation-Cognition Interaction
* 6.3.1. Background
* 6.3.2. Task and Data
* 6.3.3. Simulation Setup
* 6.3.4. Simulation Results
* 6.3.5. Discussion
* 6.4. Modeling Human Personality
* 6.4.1. Background
* 6.4.2. Principles of Personality Within CLARION
* 6.4.2.1. Principles and Justifications
* 6.4.2.2. Explaining Personality within CLARION
* 6.4.3. Simulations of Personality
* 6.4.3.1. Simulation 1
* 6.4.3.2. Simulation 2
* 6.4.3.3. Simulation 3
* 6.4.4. Discussion
* 6.5. Accounting for Human Moral Judgment
* 6.5.1. Background
* 6.5.2. Human Data
* 6.5.2.1. Effects of Personal Physical Force
* 6.5.2.2. Effects of Intention
* 6.5.2.3. Effects of Cognitive Load
* 6.5.3. Two Contrasting Views
* 6.5.3.1. Details of Model 1
* 6.5.3.2. Details of Model 2
* 6.5.4. Discussion
* 6.6. Accounting for Emotion
* 6.6.1. Issues of Emotion
* 6.6.2. Emotion and Motivation
* 6.6.3. Emotion and the Implicit-Explicit Distinction
* 6.6.4. Effects of Emotion
* 6.6.5. Emotion Generation and Regulation
* 6.6.6. Discussion
* 6.7. General Discussion
* Chapter 7. Cognitive Social Simulation
* 7.1. Introduction and Background
* 7.2. Cognition and Survival
* 7.2.1. Tribal Society Survival Task
* 7.2.2. Simulation Setup
* 7.2.3. Simulation Results and Analysis
* 7.2.3.1. Effects of Social and Environmental Factors
* 7.2.3.2. Effects of Cognitive Factors
* 7.2.4. Discussion
* 7.3. Motivation and Survival
* 7.3.1. Simulation Setup
* 7.3.2. Simulation Results and Analysis
* 7.3.2.1. Effects of Social and Environmental Factors
* 7.3.2.2. Effects of Cognitive Factors
* 7.3.2.3. Effects of Motivational Factors
* 7.3.3. Discussion
* 7.4. Organizational Decision Making
* 7.4.1. Organizational Decision Task
* 7.4.2. Simulations and Results
* 7.4.2.1. Simulation I: Matching Human Data
* 7.4.2.2. Simulation II: Extending Simulation Temporally
* 7.4.2.3. Simulation III: Varying Cognitive Parameters
* 7.4.2.4. Simulation IV: Introducing Individual Differences
* 7.4.3. Discussion
* 7.5. Academic Publishing
* 7.5.1. Academic Science
* 7.5.2. Simulation Setup
* 7.5.3. Simulation Results and Analysis
* 7.5.4. Discussion
* 7.6. General Discussion
* 7.6.1. Theoretical Issues in Cognitive Social Simulation
* 7.6.2. Challenges
* 7.6.3. Concluding Remarks
* Chapter 8. Some Important Questions and Their Short Answers
* 8.1. Theoretical Questions
* 8.2. Computational Questions
* 8.3. Biological Connections
* Chapter 9. General Discussions and Conclusions
* 9.1. A Summary of the Cognitive Architecture
* 9.2. A Discussion of the Methodologies
* 9.3. Relations to Some Important Notions
* 9.4. Relations to Some Existing Approaches
* 9.5. Comparisons with Other Cognitive Architectures
* 9.6. Future Directions
* 9.6.1. Directions for Cognitive Social Simulation
* 9.6.2. Other Directions for Cognitive Architectures
* 9.6.3. Final Words on Future Directions
* References