Memory and a priori best strategy in complex adaptive systems

Authored by M Quito, C Monterola, C Saloma

DOI: 10.1002/cplx.20008

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Model Documentation: Other Narrative

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Abstract

We employ an agent-based model to show that memory and the absence of an a priori best strategy are sufficient for self-segregation and clustering to emerge in a complex adaptive system with discrete agents that do not compete over a limited resource nor contend in a winner-take-all scenario. An agent starts from a corner of a two-dimensional lattice and aims to reach a randomly selected site in the opposite side within the shortest possible time. The agent is isolated during the course of its journey and does not interact with other agents. Time-bound obstacles appear at random lattice locations and the agent must decide whether to challenge or evade any obstacle blocking its path. The agent is capable of adapting a strategy in dealing with an obstacle. We analyze the dependence of strategy-retention time with strategy for both memory-based and memory-less agents. We derive the equality spectrum to establish the environmental conditions that favor the existence of an a priori best strategy. We found that memory-less agents do not polarize into two opposite strategy-retention time distributions nor cluster toward a center distribution. (c) 2004 Wiley Periodicals, Inc.

Tags

Clustering Strategy equality spectrum memory-less agents retention time self-segregation