Foreword |
Preface |
Acknowledgments |
The Psychological Basis of Cognitive Modeling / Chapter 1: |
Introduction / 1.1: |
Cognitive Models of Pattern Recognition / 1.2: |
Template-Matching Theory / 1.2.1: |
Prototype-Matching Theory / 1.2.2: |
Feature-Based Approach for Pattern Recognition / 1.2.3: |
The Computational Approach / 1.2.4: |
Cognitive Models of Memory / 1.3: |
Atkinson-Shiffrin's Model / 1.3.1: |
Debates on Atkinson-Shiffrin's Model / 1.3.2: |
Tulving's Model / 1.3.3: |
The Parallel Distributed Processing Approach / 1.3.4: |
Mental Imagery / 1.4: |
Mental Representation of Imagery / 1.4.1: |
Rotation of Mental Imagery / 1.4.2: |
Imagery and Size / 1.4.3: |
Imagery and Shape / 1.4.4: |
Part-Whole Relationship in Mental Imagery / 1.4.5: |
Ambiguity in Mental Imagery / 1.4.6: |
Neurophysiological Similarity between Imagery and Perception / 1.4.7: |
Cognitive Maps of Mental Imagery / 1.4.8: |
Understanding a Problem / 1.5: |
Steps in Understanding a Problem / 1.5.1: |
A Cybernetic View of Cognition / 1.6: |
The States of Cognition / 1.6.1: |
Computational Modeling of Cognitive Systems / 1.7: |
Petri Nets: A Brief Review / 1.8: |
Extension of Petri Net Models for Distributed Modeling of Cognition / 1.9: |
Scope of the Book / 1.10: |
Summary / 1.11: |
Exercises |
References |
Parallel and Distributed Logic Programming / Chapter 2: |
Formal Definitions / 2.1: |
Preliminary Definitions / 2.2.1: |
Properties of the Substitution Set / 2.2.2: |
SLD Resolution / 2.2.3: |
Concurrency in Resolution / 2.3: |
Types of Concurrent Resolution / 2.3.1: |
Petri Net Model for Concurrent Resolution / 2.4: |
Extended Petri Net / 2.4.1: |
Algorithm for Concurrent Resolution / 2.4.2: |
Performance Analysis of Petri Net-Based Models / 2.5: |
The Speed-up / 2.5.1: |
The Resource Utilization Rate / 2.5.2: |
Resource Unlimited Speed-up and Utilization Rate / 2.5.3: |
Conclusions / 2.6: |
Distributed Reasoning by Fuzzy Petri Nets: A Review / Chapter 3: |
Fuzzy Logic and Approximate Reasoning / 3.1: |
Structured Models of Approximate Reasoning / 3.2: |
Looney's Model / 3.3: |
The Model Proposed by Chen et al / 3.4: |
Konar and Mandal's Model / 3.5: |
Yu's Model / 3.6: |
Chen's Model for Backward Reasoning / 3.7: |
Bugarin and Barro's Model / 3.8: |
Pedrycz and Gomide's Learning Model / 3.9: |
Construction of Reduction Rules Using FPN / 3.10: |
Scope of Extension of Fuzzy Reasoning on Petri Nets / 3.11: |
Belief Propagation and Belief Revision Models in Fuzzy Petri Nets / 3.12: |
Imprecision Management in an Acyclic FPN / 4.1: |
Formal Definitions and the Proposed Model / 4.2.1: |
Proposed Model for Belief Propagation / 4.2.2: |
Proposed Algorithm for Belief Propagation / 4.2.3: |
Properties of FPN and Belief Propagation Scheme / 4.2.4: |
Imprecision and Inconsistency Management in a Cyclic FPN / 4.3: |
Proposed Model for Belief Revision / 4.3.1: |
Stability Analysis of the Belief Revision Model / 4.3.2: |
Detection and Elimination of Limit Cycles / 4.3.3: |
Nonmonotonic Reasoning in an FPN / 4.3.4: |
Building Expert Systems Using Fuzzy Petri Nets / 4.4: |
The Database / 5.1: |
The Data-tree / 5.2.1: |
The Knowledge Base / 5.3: |
The Inference Engine / 5.4: |
Searching Antecedent Parts of PR in the Data-tree / 5.4.1: |
Formation of the FPN / 5.4.2: |
Decision Making and Explanation Tracing / 5.4.3: |
A Case Study / 5.5: |
Performance Evaluation / 5.6: |
Time-Complexisty for the Default-Data-Tree-Formation Procedure / 5.6.1: |
Time-Complexity for the Procedure Suspect-Identification / 5.6.2: |
Time-Complexity for the Procedure Variable-Instantiation-of-PRs / 5.6.3: |
Time-Complexity for the Procedure Create-tree / 5.6.4: |
Time-Complexity for the Procedure Search-on-Data-Tree / 5.6.5: |
Time-Complexity for the Procedure FPN-Formation / 5.6.6: |
Time-Complexity for the Belief-Revision and Limit-Cycle-Detection Procedure / 5.6.7: |
Time-Complexity Analysis for the Procedure Limit-Cycle-Elimination / 5.6.8: |
Time-Complexity for the Procedure Nonmonotonic Reasoning / 5.6.9: |
Time-Complexity for the Procedure Decision-Making and Explanation Tracing / 5.6.10: |
Time-Complexity of the Overall Expert System / 5.6.11: |
Distributed Learning Using Fuzzy Cognitive Maps / 5.7: |
Axelord's Cognitive Maps / 6.1: |
Kosko's Model / 6.3: |
Kosko's Extended Model / 6.4: |
Adaptive FCMs / 6.5: |
Zhang, Chen, and Bezdek's Model / 6.6: |
Pal and Konar's FCM Model / 6.7: |
Unsupervised Learning by Fuzzy Petri Nets / 6.8: |
The Proposed Model for Cognitive Learning / 7.1: |
Encoding of Weights / 7.2.1: |
The Recall Model / 7.2.2: |
State-Space Formulation / 7.3: |
State-Space Model for Belief Updating / 7.3.1: |
State-Space Model for FTT Updating of Transitions / 7.3.2: |
State-Space Model for Weights / 7.3.3: |
Stability Analysis of the Cognitive Model / 7.4: |
Computer Simulation / 7.5: |
Implication of the Results / 7.6: |
Knowledge Refinement by Hebbian Learning / 7.7: |
The Encoding Model / 7.7.1: |
The Recall/Reasoning Model / 7.7.2: |
Case Study by Computer Simulation / 7.7.3: |
Supervised Learning by a Fuzzy Petri Net / 7.7.4: |
Proposed Model of Fuzzy Petri Nets / 8.1: |
Algorithm for Training / 8.2.1: |
Analysis of Convergence / 8.4: |
Application in Fuzzy Pattern Recognition / 8.5: |
Distributed Modeling of Abduction, Reciprocity, and Duality by Fuzzy Petri Nets / 8.6: |
State-Space Formulation of the Proposed FPN Model / 9.1: |
The Behavioral Model of FPN / 9.3.1: |
State-Space Formulation of the Model / 9.3.2: |
Special Cases of the Model / 9.3.3: |
Stability Analysis / 9.4: |
Forward Reasoning in FPNs / 9.5: |
Abductive Reasoning in FPN / 9.6: |
Bi-directional Reasoning in an FPN / 9.7: |
Fuzzy Modus Tollens and Duality / 9.8: |
Human Mood Detection and Control: A Cybernetic Approach / 9.9: |
Filtering, Segmentation and Localization of Facial Components / 10.1: |
Segmentation of the Mouth Region / 10.2.1: |
Segmentation of the Eye Region / 10.2.2: |
Segmentation of Eyebrow Constriction / 10.2.3: |
Determination of Facial Attributes / 10.3: |
Determination of the Mouth-Opening / 10.3.1: |
Determination of the Eye-Opening / 10.3.2: |
Determination of the Length of Eyebrow-Constriction / 10.3.3: |
Fuzzy Relational Model for Mood Detection / 10.4: |
Fuzzification of Facial Attributes / 10.4.1: |
The Fuzzy Relational Model for Mood Detection / 10.4.2: |
Validation of System Performance / 10.5: |
A Basic Scheme of Human Mood Control / 10.6: |
A Simple Model of Human Mood Transition Dynamics / 10.7: |
The Model / 10.7.1: |
Properties of the Model / 10.7.2: |
The Proportional Model of Human Mood Control / 10.8: |
Mamdani's Model for Mood Control / 10.9: |
Ranking the Music, Audio, and Video Clips / 10.10: |
Experimental Results / 10.11: |
Distributed Planning and Multi-agent Coordination of Robots / 10.12: |
Single-Agent Planning / 11.1: |
Multi-Agent Planning / 11.3: |
Task Sharing and Distribution in Multi-agent Planning / 11.3.1: |
Cooperation with/without Communication / 11.3.2: |
Homogeneous and Heterogeneous Distributed Planning / 11.3.3: |
Vision-based Transportation of Blocks by Two Robots / 11.4: |
Timing Analysis of the Transportation Problem / 11.5: |
Analysis with Two agents / 11.6.1: |
Analysis with /-agents / 11.6.2: |
Index / 11.7: |