In Yukio Ohsawa Peter McBurney (ed.), Chance Discovery by Machines. Springer-Verlag, pp. 208-230. (2003)

Authors
Eric Dietrich
State University of New York at Binghamton
Abstract
Analogical reminding in humans and machines is a great source for chance discoveries because analogical reminding can produce representational change and thereby produce insights. Here, we present a new kind of representational change associated with analogical reminding called packing. We derived the algorithm in part from human data we have on packing. Here, we explain packing and its role in analogy making, and then present a computer model of packing in a micro-domain. We conclude that packing is likely used in human chance discoveries, and is needed if our machines are to make their own chance discoveries.
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References found in this work BETA

Fundamental Aspects of Cognitive Representation.Stephen Palmer - 1978 - In Eleanor Rosch & Barbara Lloyd (eds.), Cognition and Categorization. Lawrence Elbaum Associates. pp. 259-303.

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Citations of this work BETA

Toward Extending the Relational Priming Model: Six Questions.Eric Dietrich - 2008 - Behavioral and Brain Sciences 31 (4):383-384.
Developing Structured Representations.Leonidas A. A. Doumas & Lindsey E. Richland - 2008 - Behavioral and Brain Sciences 31 (4):384-385.

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