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Entropy 2014, 16(6), 3357-3378; doi:10.3390/e16063357

Effects of Anticipation in Individually Motivated Behaviour on Survival and Control in a Multi-Agent Scenario with Resource Constraints

Department of Computer Science, University of Hertfordshire, College Lane, Hatfield HertsAL10 9AB, UK
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Received: 1 March 2014 / Revised: 21 March 2014 / Accepted: 10 June 2014 / Published: 19 June 2014
(This article belongs to the Special Issue Entropy Methods in Guided Self-Organization)
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Abstract

Self-organization and survival are inextricably bound to an agent’s ability to control and anticipate its environment. Here we assess both skills when multiple agents compete for a scarce resource. Drawing on insights from psychology, microsociology and control theory, we examine how different assumptions about the behaviour of an agent’s peers in the anticipation process affect subjective control and survival strategies. To quantify control and drive behaviour, we use the recently developed information-theoretic quantity of empowerment with the principle of empowerment maximization. In two experiments involving extensive simulations, we show that agents develop risk-seeking, risk-averse and mixed strategies, which correspond to greedy, parsimonious and mixed behaviour. Although the principle of empowerment maximization is highly generic, the emerging strategies are consistent with what one would expect from rational individuals with dedicated utility models. Our results support empowerment maximization as a universal drive for guided self-organization in collective agent systems. View Full-Text
Keywords: artificial life; artificial societies; resource scarcity; guided self-organization; adaptive systems; empowerment artificial life; artificial societies; resource scarcity; guided self-organization; adaptive systems; empowerment
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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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Guckelsberger, C.; Polani, D. Effects of Anticipation in Individually Motivated Behaviour on Survival and Control in a Multi-Agent Scenario with Resource Constraints. Entropy 2014, 16, 3357-3378.

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