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Games 2015, 6(4), 604-636; doi:10.3390/g6040604

The Role of Implicit Motives in Strategic Decision-Making: Computational Models of Motivated Learning and the Evolution of Motivated Agents

School of Engineering and Information Technology, University of New South Wales, Canberra 2600, Australia
Academic Editor: Andrew M. Colman
Received: 18 August 2015 / Revised: 12 October 2015 / Accepted: 30 October 2015 / Published: 12 November 2015
(This article belongs to the Special Issue Psychological Aspects of Strategic Choice)
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Abstract

Individual behavioral differences in humans have been linked to measurable differences in their mental activities, including differences in their implicit motives. In humans, individual differences in the strength of motives such as power, achievement and affiliation have been shown to have a significant impact on behavior in social dilemma games and during other kinds of strategic interactions. This paper presents agent-based computational models of power-, achievement- and affiliation-motivated individuals engaged in game-play. The first model captures learning by motivated agents during strategic interactions. The second model captures the evolution of a society of motivated agents. It is demonstrated that misperception, when it is a result of motivation, causes agents with different motives to play a given game differently. When motivated agents who misperceive a game are present in a population, higher explicit payoff can result for the population as a whole. The implications of these results are discussed, both for modeling human behavior and for designing artificial agents with certain salient behavioral characteristics. View Full-Text
Keywords: motivation; game theory; learning; evolution motivation; game theory; learning; evolution
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Merrick, K. The Role of Implicit Motives in Strategic Decision-Making: Computational Models of Motivated Learning and the Evolution of Motivated Agents. Games 2015, 6, 604-636.

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