Engineering Intelligent Systems: Concepts, Theory, and Applications
Overview of intelligent systems that shows how current concepts & techniques in engineering, mathematics, & neurophysiology contribute to designing intelligent systems. Covers: computer vision, robotics, pattern recognition, adaptive control, & intelligent systems design.
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GAME PLAYING AND MACHINES
REASON LOGIC AND MATHEMATICS
COMPUTERS AND AUTOMATA
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adaptive control algebra of classes algorithm applied artificial intelligence associated automata automata models automaton behavior binary Boolean algebra called cell channel Chapter code word computer vision concepts consider control system Cybernetics decision defined definition described discriminant functions elements environment error evaluation example false proposition finite fuzzy set game trees heuristic IEEE illustrated in Figure industrial robots input interval labeled learning automata linear linearly separable LR P automaton Markov chain matrix mean turnaround memory minterms module move neuron node operation output parameters pattern recognition performance player possible Postulate problem procedure processor propositional calculus pulse queue queueing theory random realization reliability representation requires scheduling discipline self-organizing self-repair sensors sequence sequential shown in Figure signal specific stochastic automata switching symbols tape expression task techniques theorem theory threshold logic Turing machine variables vector Venn diagram vision system weight winning