Titlebook: Human and Machine Problem Solving; K. J. Gilhooly Book 1989 Plenum Press, New York 1989 Action.Memory.Problem Solving.Processing.algorithm

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Machine Learning,ncepts merely from unstructured observations or by planning and performing experiments in the environment. There is no teacher involved here, and all the burden is on the learner. The learner’s environment plays the role of an oracle.

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ur­ ring problem solving into hypothetical processes, while AI seeks to synthesize problem-solving performance from well-defined processes. Psychology may suggest possible processes to AI and, in turn, AI may suggest plausible hypotheses to psychology. It should be useful for both sides to have some

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Human and Machine Problem Solving Toward a Comparative Cognitive Science,ble effort has been invested in automating problem-solving processes in a number of task areas. These efforts form part of the field of . (AI), which attempts to construct programs that can carry out complex performances hitherto the preserve of humans and other organisms.

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Adversary Problem Solving by Humans,l replies; we can respond to each of these replies, but each response will engender a further set of replies. Hence, the search tree grows exponentially. A complete solution to the problem is often beyond our reach, and beyond the resources of a computer, with the result that our decisions must be based on heuristic principles.

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Book 1989urrent computers have rather different functional or cognitive architectures. Thus, insights into the role of cognitive ar­ chitecture in performance may be gained by comparing typical human problem solving with efficient machine problem solving over a range of tasks. Readers may notice that there i

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