Machine discovery

Foundations of Science 1 (2):171-200 (1995)
Human and machine discovery are gradual problem-solving processes of searching large problem spaces for incompletely defined goal objects. Research on problem solving has usually focused on search of an instance space (empirical exploration) and a hypothesis space (generation of theories). In scientific discovery, search must often extend to other spaces as well: spaces of possible problems, of new or improved scientific instruments, of new problem representations, of new concepts, and others. This paper focuses especially on the processes for finding new problem representations and new concepts, which are relatively new domains for research on discovery.Scientific discovery has usually been studied as an activity of individual investigators, but these individuals are positioned in a larger social structure of science, being linked by the blackboard of open publication (as well as by direct collaboration). Even while an investigator is working alone, the process is strongly influenced by knowledge and skills stored in memory as a result of previous social interaction. In this sense, all research on discovery, including the investigations on individual processes discussed in this paper, is social psychology, or even sociology.
Keywords Machine discovery  Heuristic search  Concept discovery  Psychology of discovery  Representation  Analogy  Mutilated Checkerboard  Surprise heuristic  Learning from examples  Intuition
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DOI 10.1007/BF00124609
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References found in this work BETA
Peter Spirtes, Clark Glymour & Richard Scheines (1996). Causation, Prediction, and Search. British Journal for the Philosophy of Science 47 (1):113-123.
George Pólya (1968). Mathematics and Plausible Reasoning. Princeton, N.J.,Princeton University Press.

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