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  • scientific discovery  (2)
  • Psychology of discovery  (1)
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Foundations of science 1 (1995), S. 171-200 
    ISSN: 1572-8471
    Keywords: Machine discovery ; Heuristic search ; Concept discovery ; Psychology of discovery ; Representation ; Analogy ; Mutilated Checkerboard ; Surprise heuristic ; Learning from examples ; Intuition
    Source: Springer Online Journal Archives 1860-2000
    Topics: Natural Sciences in General
    Notes: Abstract 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.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 1 (1986), S. 107-137 
    ISSN: 0885-6125
    Keywords: scientific discovery ; componential models ; recovering from inconsistencies ; history of chemistry ; phlogisten theory
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract One of the major goals of 18th century chemistry was to determine the components of substances. In this paper we describe STAHL, a system that models significant portions of 18th century reasoning about compositional models. The system includes a number of heuristics for generating componential models from reactions, as well as error recovery mechanisms for dealing with inconsistent results. STAHL processes chemical reactions incrementally, and is therefore capable of reconstructing extended historic episodes, such as the century-long development of the phlogiston theory. We evaluate STAHL’s heuristics in the light of historical data, and conclude that the same reasoning mechanisms account for a variety of historical achievements, including Black’s models of mild alkali and Lavoisier’s oxygen theory. STAHL explains the generation of competing accounts of the same reactions, since the system’s reasoning chain depends on knowledge it has accumulated at earlier stages.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 1 (1986), S. 107-137 
    ISSN: 0885-6125
    Keywords: scientific discovery ; componential models ; recovering from inconsistencies ; history of chemistry ; phlogisten theory
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract One of the major goals of 18th century chemistry was to determine the components of substances. In this paper we describe STAHL, a system that models significant portions of 18th century reasoning about compositional models. The system includes a number of heuristics for generating componential models from reactions, as well as error recovery mechanisms for dealing with inconsistent results. STAHL processes chemical reactions incrementally, and is therefore capable of reconstructing extended historic episodes, such as the century-long development of the phlogiston theory. We evaluate STAHL’s heuristics in the light of historical data, and conclude that the same reasoning mechanisms account for a variety of historical achievements, including Black’s models of mild alkali and Lavoisier’s oxygen theory. STAHL explains the generation of competing accounts of the same reactions, since the system’s reasoning chain depends on knowledge it has accumulated at earlier stages.
    Type of Medium: Electronic Resource
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
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