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Intelligent engineering systems and computational cybernetics
A further important component of machine intelligence is a kind of “structural uniformity” giving room and possibility to model arbitrary particular details a priori not specified and unknown.This idea is similar to the ready-to-wear industry, which introduced products, which can be slightly modified later on in contrast to tailor-made creations aiming at maximum accuracy from the beginning. These subsequent corrections can be carried out by machines automatically. This “learning ability” is a key element of machine intelligence.The past decade confirmed that the view of typical components of the present soft computing as fuzzy logic, neural computing.
Cognitive engineering : A distributed approach to machine intelligence
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.
