On the Parallel Between Learning and Evolution

Pringle, J. W. S.

doi:10.1163/156853951x00269

Cited by 258 publications

(74 citation statements)

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“…The consistency of the trend toward fit and the general goodness of fit achieved have tempted some writers to teleological explanations, or to explanations involving prescience on the part of the animal in small or large degree. Ashby (3) and Pringle (22) have explicitly proposed that the blind variation and selective survival model be applied to adaptation at the level of animal problem solving and learning. 2 There are differences in satisfactory in not specifying how the control comes about.…”

Section: Selective Survival In Problem Solving or Learningmentioning

confidence: 99%

Perception as substitute trial and error.

Campbell¹

1956

Psychological Review

120

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Section: Selective Survival In Problem Solving or Learningmentioning

confidence: 99%

Perception as substitute trial and error.

Campbell¹

1956

Psychological Review

120

View full text Add to dashboard Cite

“…Simon has framed individual learning in the same terms as evolution, cf. also [60], so the same elucidation should be helpful in understanding both developmental and learning processes.…”

Section: Six Views On Embodied Cognition and Simon's Two Environmentsmentioning

confidence: 99%

Situatedness and Embodiment of Computational Systems

Miłkowski

2017

Entropy

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Abstract:In this paper, the role of the environment and physical embodiment of computational systems for explanatory purposes will be analyzed. In particular, the focus will be on cognitive computational systems, understood in terms of mechanisms that manipulate semantic information. It will be argued that the role of the environment has long been appreciated, in particular in the work of Herbert A. Simon, which has inspired the mechanistic view on explanation. From Simon's perspective, the embodied view on cognition seems natural but it is nowhere near as critical as its proponents suggest. The only point of difference between Simon and embodied cognition is the significance of body-based off-line cognition; however, it will be argued that it is notoriously over-appreciated in the current debate. The new mechanistic view on explanation suggests that even if it is critical to situate a mechanism in its environment and study its physical composition, or realization, it is also stressed that not all detail counts, and that some bodily features of cognitive systems should be left out from explanations.

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“…The latter, in turn, followed the analogy of evolution and learning [57,58]. Simonton's theory stipulates three stages of problem solving: blind variation, selection and retention.…”

Section: Models Of Creative Problem Solvingmentioning

confidence: 99%

Deciphering the Enigma of Human Creativity: Can a Digital Computer Think?

Hong¹

2013

J Comput Sci Syst Biol

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The objective of the present article is a) to explain humans' high creativity in non-mystic and unambiguous terms, b) to evaluate the performance of problem-solving computer programs and c) to make suggestions about future designs of heuristics. Unlike many previous attempts in the past century, we sought inspiration from two sources that had been neglected or excluded from considerations by experts: artificial intelligence and introspections of a number of highly creative individuals, who confessed that they had a penchant for visual thinking. Simonton's chance-configuration model was refurbished accordingly. It is now possible for the refurbished model to explain a number of outstanding puzzles that had eluded our predecessors: a) what intuition is, b) why creators had no idea about their source of inspiration even after the fact, c) a peculiar event happening at the discovery time, known as the "aha" phenomenon, d) a type of accidental discoveries known as serendipity. Moreover, the elusive concept of abduction advanced by philosopher Charles Peirce is actually visual thinking in disguise. Blessed with this new understanding, we could evaluate the performance of a number of problem-solving computer programs from a cognitive point of view. It turned out that the common thread that links human creativity and computerbased creative problem solving is heuristic searching. Recognizing that a digital computer must perform heuristic searching in a digital environment, which is not the most user-friendly environment to do so, we made suggestions about how to circumvent the restrictions without sacrificing the principles in future designs of heuristics.

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On the Parallel Between Learning and Evolution

Cited by 258 publications

References 0 publications

Perception as substitute trial and error.

Perception as substitute trial and error.

Situatedness and Embodiment of Computational Systems

Deciphering the Enigma of Human Creativity: Can a Digital Computer Think?

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