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Adm. Sci. 2013, 3(3), 53-75; doi:10.3390/admsci3030053

Individual Learning and Social Learning: Endogenous Division of Cognitive Labor in a Population of Co-evolving Problem-Solvers

Department of Economics, Cleveland State University, Cleveland, OH 44115, USA
Department of Business Economics and Public Policy, The Wharton School, University of Pennsylvania, Philadelphia, PA 19102, USA
Author to whom correspondence should be addressed.
Received: 17 May 2013 / Revised: 28 June 2013 / Accepted: 2 July 2013 / Published: 12 July 2013
(This article belongs to the Special Issue Computational Organization Theory)
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The dynamic choice between individual and social learning is explored for a population of autonomous agents whose objective is to find solutions to a stream of related problems. The probability that an agent is in the individual learning mode, as opposed to the social learning mode, evolves over time through reinforcement learning. Furthermore, the communication network of an agent is also endogenous. Our main finding is that when agents are sufficiently effective at social learning, structure emerges in the form of specialization. Some agents focus on coming up with new ideas while the remainder of the population focuses on imitating worthwhile ideas. View Full-Text
Keywords: individual learning; social learning; organizational learning individual learning; social learning; organizational learning

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Chang, M.-H.; Harrington, J.E., Jr. Individual Learning and Social Learning: Endogenous Division of Cognitive Labor in a Population of Co-evolving Problem-Solvers. Adm. Sci. 2013, 3, 53-75.

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