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. Computer simulations are also included in most chapters to give a clear idea about the application of the algorithms undertaken in the book.

Comprehensive presentation of neuro-fuzzy learning, logic programming and Bayesian reasoning Includes both classical results as well as new developments Includes supplementary material: sn.pub/extras

Autorentext

Dr. Pratyusha Rakshit received her B.Tech. degree in Electronics and Communication Engineering (ECE) from the Institute of Engineering and Management, Kolkata, India, and her M.E. degree in Control Engineering from the Department of Electronics and Telecommunication Engineering (ETCE), Jadavpur University, Kolkata, India in 2010 and 2012, respectively. She was awarded her Ph.D. (Engineering) degree from Jadavpur University, India, in 2016 and is currently an Assistant Professor at its ETCE Department. She was awarded Gold Medals for securing the highest marks in B.Tech. in ECE and among all the courses of M.E. respectively in 2010 and 2012. She was the recipient of the CSIR Senior Research Fellowship, INSPIRE Fellowship and UGC UPE-II Junior Research Fellowship. Her principal research interests include artificial and computational intelligence, evolutionary computation, robotics, bioinformatics, pattern recognition, fuzzy logic, cognitive science and human-computer interaction. She is the author of over 50 papers published in top international journals and conference proceedings. She also serves as a reviewer for IEEE-TFS, IEEE-SMC: Systems, Neurocomputing, Information Sciences, and Applied Soft Computing. Dr. Amit Konar is currently a Professor at the Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India. Dr. Konar is the author of over 350 publications, including books/monographs, peer-reviewed book chapters and papers, all with leading international publishers. He is an Associate Editor of several prestigious journals, including IEEE Transactions, Elsevier, Springer and IOS Press, the Netherlands. He has undertaken several prestigious research projects, including UGC's departmental research support (DRS) scheme, DIT's national project on Perception Engineering and UGC's excellence program in Cognitive Science. Dr. Konar was a recipient of the AICTE-accredited 1997-2000 Career Award for young teachers. He has been nominated as a Fellow of the National Academy of Engineering, and his current research interests include human-computer interfacing, cognitive neuroscience, robotics and machine intelligence.

Klappentext

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. Computer simulations are also included in most chapters to give a clear idea about the application of the algorithms undertaken in the book.

Inhalt
The Psychological Basis of Cognitive Modeling.- Parallel and Distributed Logic Programming.- Distributed Reasoning by Fuzzy Petri Nets: A Review.- Belief Propagation and Belief Revision Models in Fuzzy Petri Nets.- Building Expert Systems Using Fuzzy Petri Nets.- Distributed Learning Using Fuzzy Cognitive Maps.- Unsupervised Learning by Fuzzy Petri Nets.- Supervised Learning by a Fuzzy Petri Net.- Distributed Modeling of Abduction, Reciprocity, and Duality by Fuzzy Petri Nets.- Human Mood Detection and Control: A Cybernetic Approach.- Distributed Planning and Multi-agent Coordination of Robots.