Tyugu (cybernetics, Tallinn U. of Technology, Estonia) reviews methods of searching, learning, problem solving and decision making in artificial intelligence (AI) systems, concentrating on mature architectures and algorithms. He describes how AI systems (and humans) handle knowledge, covering such topics as brute force deduction, causal calculi and resolution, decision tables, the Rete algorithm, frames, and describes search methods (including the Vitterby algorithms) the processes of learning and decision making (including learning for adaptation, symbolic learning, massive parallel learning, and data clustering), and problem solving and planning (including consistency algorithms, propagation algorithms, algorithms of constraint solving, program synthesis, planning and using intelligent agents). Intended as a handbook for application developers, this also works well as a classroom text. Readers should have a strong background in computer terminology.
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