Cognitive Engineering

A Distributed Approach to Machine Intelligence

By: Amit Konar

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Hardcover | 8 September 2005

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372 Pages

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24.13 x 15.88 x 2.54

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What we profoundly witness these days is a growing number of human-centric systems and a genuine interest in a comprehensive understanding of their underlying paradigms and the development of solid and efficient design practices. We are indeed in the midst of the next information revolution, which very likely brings us into a completely new world of ubiquitous and invisible computing, Ambient Intelligent (AMI), and wearable hardware. This requires a totally new way of thinking in which cognitive aspects of design, cognitive system engineering and distributed approach play a pivotal role. This book fully addresses these timely needs by filling a gap between the two well-established disciplines of cognitive sciences and cognitive systems engineering. As we put succinctly in the preface, with the psychological perspective of human cognition in mind, "the book explores the computational models of reasoning, learning, planning and multi-agent coordination and control of the human moods". This is an excellent, up to the point description of the book. The treatise is focused on the underlying fundamentals, spans across a vast territory embracing logic perspectives of human cognition, distributed models, parallel computing, expert systems, and intelligent robotics.

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You Can Find This Book In

Non-Fiction Science Science in General Engineering & Technology Technology in General Computing & I.T.Computer Science Artificial Intelligence Electronics & Communications Engineering Communications Engineering & Telecommunications Psychology Cognition & Cognitive Psychology

Computer Programming & Software Development Algorithms & Data Structures Databases Data Capture & Analysis Graphical & Digital Media Applications 3D Graphics & Modelling

Foreword	p. V
Preface	p. vii
Acknowledgments	p. xi
The Psychological Basis of Cognitive Modeling
Introduction	p. 1
Cognitive Models of Pattern Recognition	p. 3
Template-Matching Theory	p. 3
Prototype-Matching Theory	p. 4
Feature-Based Approach for Pattern Recognition	p. 4
The Computational Approach	p. 5
Cognitive Models of Memory	p. 6
Atkinson-Shiffrin's Model	p. 6
Debates on Atkinson-Shiffrin's Model	p. 8
Tulving's Model	p. 8
The Parallel Distributed Processing Approach	p. 11
Mental Imagery
Mental Representation of Imagery	p. 12
Rotation of Mental Imagery	p. 12
Imagery and Size	p. 13
Imagery and Shape	p. 14
Part-Whole Relationship in Mental Imagery	p. 14
Ambiguity in Mental Imagery	p. 15
Neurophysiological Similarity between Imagery and Perception	p. 15
Cognitive Maps of Mental Imagery	p. 15
Understanding a Problem	p. 17
Steps in Understanding a Problem	p. 18
A Cybernetic View of Cognition	p. 19
The States of Cognition	p. 20
Computational Modeling of Cognitive Systems	p. 24
Petri Nets: A Brief Review	p. 25
Extension of Petri Net Models for Distributed Modeling of Cognition	p. 29
Scope of the Book	p. 31
Summary	p. 31
Exercises	p. 32
References	p. 35
Parallel and Distributed Logic Programming
Introduction	p. 39
Formal Definitions	p. 41
Preliminary Definitions	p. 41
Properties of the Substitution Set	p. 45
SLD Resolution	p. 47
Concurrency in Resolution	p. 52
Preliminary Definitions	p. 52
Types of Concurrent Resolution	p. 55
Petri Net Model for Concurrent Resolution	p. 61
Extended Petri Net	p. 61
Algorithm for Concurrent Resolution	p. 63
Performance Analysis of Petri Net-Based Models	p. 67
The Speed-up	p. 67
The Resource Utilization Rate	p. 68
Resource Unlimited Speed-up and Utilization Rate	p. 69
Conclusions	p. 70
Exercises	p. 70
References	p. 82
Distributed Reasoning by Fuzzy Petri Nets: A Review
Fuzzy Logic and Approximate Reasoning	p. 85
Structured Models of Approximate Reasoning	p. 87
Looney's Model	p. 89
The Model Proposed by Chen et al	p. 91
Konar and Mandal's Model	p. 93
Yu's Model	p. 97
Chen's Model for Backward Reasoning	p. 100
Bugarin and Barro's Model	p. 102
Pedrycz and Gomide's Learning Model	p. 107
Construction of Reduction Rules Using FPN	p. 110
Scope of Extension of Fuzzy Reasoning on Petri Nets	p. 115
Summary	p. 116
Exercises	p. 117
References	p. 121
Belief Propagation and Belief Revision Models in Fuzzy Petri Nets
Introduction	p. 123
Imprecision Management in an Acyclic FPN	p. 125
Formal Definitions and the Proposed Model	p. 126
Proposed Model for Belief Propagation	p. 126
Proposed Algorithm for Belief Propagation	p. 128
Properties of FPN and Belief Propagation Scheme	p. 132
Imprecision and Inconsistency Management in a Cyclic FPN	p. 134
Proposed Model for Belief Revision	p. 134
Stability Analysis of the Belief Revision Model	p. 135
Detection and Elimination of Limit Cycles	p. 141
Nonmonotonic Reasoning in an FPN	p. 144
Conclusions	p. 147
Exercises	p. 148
References	p. 151
Building Expert Systems Using Fuzzy Petri Nets
Introduction	p. 153
The Database	p. 155
The Data-tree	p. 155
The Knowledge Base	p. 157
The Inference Engine	p. 160
Searching Antecedent Parts of PR in the Data-tree	p. 160
Formation of the FPN	p. 162
Decision Making and Explanation Tracing	p. 163
A Case Study	p. 163
Performance Evaluation	p. 166
Time-Complexisty for the Default-Data-Tree-Formation Procedure	p. 166
Time-Complexity for the Procedure Suspect-Identification	p. 167
Time-Complexity for the Procedure Variable-Instantiation-of-PRs	p. 168
Time-Complexity for the Procedure Create-tree	p. 169
Time-Complexity for the Procedure Search-on-Data-Tree	p. 170
Time-Complexity for the Procedure FPN-Formation	p. 171
Time-Complexity for the Belief-Revision and Limit-Cycle-Detection Procedure	p. 173
Time-Complexity Analysis for the Procedure Limit-Cycle-Elimination	p. 174
Time-Complexity for the Procedure Nonmonotonic Reasoning	p. 175
Time-Complexity for the Procedure Decision-Making and Explanation Tracing	p. 176
Time-Complexity of the Overall Expert System	p. 177
Conclusions	p. 178
Exercises	p. 178
References	p. 179
Distributed Learning Using Fuzzy Cognitive Maps
Introduction	p. 181
Axelord's Cognitive Maps	p. 182
Kosko's Model	p. 184
Kosko's Extended Model	p. 187
Adaptive FCMs	p. 188
Zhang, Chen, and Bezdek's Model	p. 189
Pal and Konar's FCM Model	p. 191
Conclusions	p. 197
Exercises	p. 197
References	p. 201
Unsupervised Learning by Fuzzy Petri Nets
Introduction	p. 205
The Proposed Model for Cognitive Learning	p. 206
Encoding of Weights	p. 208
The Recall Model	p. 208
State-Space Formulation	p. 210
State-Space Model for Belief Updating	p. 211
State-Space Model for FTT Updating of Transitions	p. 211
State-Space Model for Weights	p. 212
Stability Analysis of the Cognitive Model	p. 212
Computer Simulation	p. 216
Implication of the Results	p. 219
Knowledge Refinement by Hebbian Learning	p. 219
The Encoding Model	p. 219
The Recall/Reasoning Model	p. 221
Case Study by Computer Simulation	p. 221
Implication of the Results	p. 226
Conclusions	p. 226
Exercises	p. 228
References	p. 229
Supervised Learning by a Fuzzy Petri Net
Introduction	p. 233
Proposed Model of Fuzzy Petri Nets	p. 234
State-Space Formulation	p. 236
Algorithm for Training	p. 238
Analysis of Convergence	p. 243
Application in Fuzzy Pattern Recognition	p. 245
Conclusions	p. 252
Exercises	p. 252
References	p. 253
Distributed Modeling of Abduction, Reciprocity, and Duality by Fuzzy Petri Nets
Introduction	p. 257
Formal Definitions	p. 259
State-Space Formulation of the Proposed FPN Model	p. 262
The Behavioral Model of FPN	p. 263
State-Space Formulation of the Model	p. 265
Special Cases of the Model	p. 266
Stability Analysis	p. 269
Forward Reasoning in FPNs	p. 272
Abductive Reasoning in FPN	p. 274
Bi-directional Reasoning in an FPN	p. 279
Fuzzy Modus Tollens and Duality	p. 288
Conclusions	p. 291
Exercises	p. 292
References	p. 293
Human Mood Detection and Control: A Cybernetic Approach
Introduction	p. 297
Filtering, Segmentation and Localization of Facial Components	p. 299
Segmentation of the Mouth Region	p. 300
Segmentation of the Eye Region	p. 302
Segmentation of Eyebrow Constriction	p. 303
Determination of Facial Attributes	p. 303
Determination of the Mouth-Opening	p. 303
Determination of the Eye-Opening	p. 304
Determination of the Length of Eyebrow-Constriction	p. 305
Fuzzy Relational Model for Mood Detection	p. 306
Fuzzification of Facial Attributes	p. 306
The Fuzzy Relational Model for Mood Detection	p. 307
Validation of System Performance	p. 309
A Basic Scheme of Human Mood Control	p. 310
A Simple Model of Human Mood Transition Dynamics	p. 311
The Model	p. 312
Properties of the Model	p. 315
The Proportional Model of Human Mood Control	p. 317
Mamdani's Model for Mood Control	p. 318
Ranking the Music, Audio, and Video Clips	p. 326
Experimental Results	p. 327
Conclusions	p. 328
Exercises	p. 328
References	p. 329
Distributed Planning and Multi-agent Coordination of Robots
Introduction	p. 331
Single-Agent Planning	p. 333
Multi-Agent Planning	p. 336
Task Sharing and Distribution in Multi-agent Planning	p. 336
Cooperation with/without Communication	p. 336
Homogeneous and Heterogeneous Distributed Planning	p. 338
Vision-based Transportation of Blocks by Two Robots	p. 339
Experimental Results	p. 341
Timing Analysis of the Transportation Problem	p. 343
Analysis with Two agents	p. 343
Analysis with /-agents	p. 345
Conclusions	p. 347
Exercises	p. 347
References	p. 348
Index	p. 351
Table of Contents provided by Publisher. All Rights Reserved.

Cognitive Engineering

A Distributed Approach to Machine Intelligence

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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