Ebook: Cognitive Engineering: A Distributed Approach to Machine Intelligence
- Tags: Artificial Intelligence (incl. Robotics), Simulation and Modeling, Symbolic and Algebraic Manipulation, Algorithm Analysis and Problem Complexity, Models and Principles, Cognitive Psychology
- Series: Advanced Information and Knowledge Processing
- Year: 2005
- Publisher: Springer-Verlag London
- Edition: 1
- Language: English
- pdf
Cognitive Engineering: A Distributed Approach to Machine Intelligence explores the design issues of intelligent engineering systems. Beginning with the foundations of psychological modeling of the human mind, the main emphasis is given to parallel and distributed realization of intelligent models for application in reasoning, learning, planning and multi-agent co-ordination problems. The last two chapters provide case studies on human-mood detection and control, and behavioral co-operation of mobile robots. This is the first comprehensive text of its kind, bridging the gap between Cognitive Science and Cognitive Systems Engineering.
Each chapter includes plenty of numerical examples and exercises with sufficient hints, so that the reader can solve the exercises on their own. Computer simulations are also included in most chapters to give a clear idea about the application of the algorithms undertaken in the book. In addition, mathematical analysis on convergence and stability of the neuro-fuzzy models will enable the reader to pursue their research career in cognitive engineering.
Cognitive Engineering: A Distributed Approach to Machine Intelligence is unique in its theme and contents, and includes a Foreword by Professor Witold Pedrycz - written with graduates in mind, this book would also be a valuable resource for researchers in the fields of Cognitive Science, Computer Science and Cognitive Engineering.
Cognitive Engineering: A Distributed Approach to Machine Intelligence explores the design issues of intelligent engineering systems. Beginning with the foundations of psychological modeling of the human mind, the main emphasis is given to parallel and distributed realization of intelligent models for application in reasoning, learning, planning and multi-agent co-ordination problems. The last two chapters provide case studies on human-mood detection and control, and behavioral co-operation of mobile robots. This is the first comprehensive text of its kind, bridging the gap between Cognitive Science and Cognitive Systems Engineering.
Each chapter includes plenty of numerical examples and exercises with sufficient hints, so that the reader can solve the exercises on their own. Computer simulations are also included in most chapters to give a clear idea about the application of the algorithms undertaken in the book. In addition, mathematical analysis on convergence and stability of the neuro-fuzzy models will enable the reader to pursue their research career in cognitive engineering.
Cognitive Engineering: A Distributed Approach to Machine Intelligence is unique in its theme and contents, and includes a Foreword by Professor Witold Pedrycz - written with graduates in mind, this book would also be a valuable resource for researchers in the fields of Cognitive Science, Computer Science and Cognitive Engineering.
Cognitive Engineering: A Distributed Approach to Machine Intelligence explores the design issues of intelligent engineering systems. Beginning with the foundations of psychological modeling of the human mind, the main emphasis is given to parallel and distributed realization of intelligent models for application in reasoning, learning, planning and multi-agent co-ordination problems. The last two chapters provide case studies on human-mood detection and control, and behavioral co-operation of mobile robots. This is the first comprehensive text of its kind, bridging the gap between Cognitive Science and Cognitive Systems Engineering.
Each chapter includes plenty of numerical examples and exercises with sufficient hints, so that the reader can solve the exercises on their own. Computer simulations are also included in most chapters to give a clear idea about the application of the algorithms undertaken in the book. In addition, mathematical analysis on convergence and stability of the neuro-fuzzy models will enable the reader to pursue their research career in cognitive engineering.
Cognitive Engineering: A Distributed Approach to Machine Intelligence is unique in its theme and contents, and includes a Foreword by Professor Witold Pedrycz - written with graduates in mind, this book would also be a valuable resource for researchers in the fields of Cognitive Science, Computer Science and Cognitive Engineering.
Content:
Front Matter....Pages I-XVIII
The Psychological Basis of Cognitive Modeling....Pages 1-38
Parallel and Distributed Logic Programming....Pages 39-84
Distributed Reasoning by Fuzzy Petri Nets: A Review....Pages 85-122
Belief Propagation and Belief Revision Models in Fuzzy Petri Nets....Pages 123-152
Building Expert Systems Using Fuzzy Petri Nets....Pages 153-180
Distributed Learning Using Fuzzy Cognitive Maps....Pages 181-204
Unsupervised Learning by Fuzzy Petri Nets....Pages 205-231
Supervised Learning by a Fuzzy Petri Net....Pages 233-255
Distributed Modeling of Abduction, Reciprocity, and Duality by Fuzzy Petri Nets....Pages 257-296
Human Mood Detection and Control: A Cybernetic Approach....Pages 297-330
Distributed Planning and Multi-agent Coordination of Robots....Pages 331-349
Back Matter....Pages 351-353
Cognitive Engineering: A Distributed Approach to Machine Intelligence explores the design issues of intelligent engineering systems. Beginning with the foundations of psychological modeling of the human mind, the main emphasis is given to parallel and distributed realization of intelligent models for application in reasoning, learning, planning and multi-agent co-ordination problems. The last two chapters provide case studies on human-mood detection and control, and behavioral co-operation of mobile robots. This is the first comprehensive text of its kind, bridging the gap between Cognitive Science and Cognitive Systems Engineering.
Each chapter includes plenty of numerical examples and exercises with sufficient hints, so that the reader can solve the exercises on their own. Computer simulations are also included in most chapters to give a clear idea about the application of the algorithms undertaken in the book. In addition, mathematical analysis on convergence and stability of the neuro-fuzzy models will enable the reader to pursue their research career in cognitive engineering.
Cognitive Engineering: A Distributed Approach to Machine Intelligence is unique in its theme and contents, and includes a Foreword by Professor Witold Pedrycz - written with graduates in mind, this book would also be a valuable resource for researchers in the fields of Cognitive Science, Computer Science and Cognitive Engineering.
Content:
Front Matter....Pages I-XVIII
The Psychological Basis of Cognitive Modeling....Pages 1-38
Parallel and Distributed Logic Programming....Pages 39-84
Distributed Reasoning by Fuzzy Petri Nets: A Review....Pages 85-122
Belief Propagation and Belief Revision Models in Fuzzy Petri Nets....Pages 123-152
Building Expert Systems Using Fuzzy Petri Nets....Pages 153-180
Distributed Learning Using Fuzzy Cognitive Maps....Pages 181-204
Unsupervised Learning by Fuzzy Petri Nets....Pages 205-231
Supervised Learning by a Fuzzy Petri Net....Pages 233-255
Distributed Modeling of Abduction, Reciprocity, and Duality by Fuzzy Petri Nets....Pages 257-296
Human Mood Detection and Control: A Cybernetic Approach....Pages 297-330
Distributed Planning and Multi-agent Coordination of Robots....Pages 331-349
Back Matter....Pages 351-353
....