Self-organization in a distributed coordination game through heuristic rules

Shubham Agarwal, Diptesh Ghosh () and Anindya S. Chakrabarti ()
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Shubham Agarwal: Indian Institute of Technology
Anindya S. Chakrabarti: Economics Area, Indian Institute of Management

The European Physical Journal B: Condensed Matter and Complex Systems, 2016, vol. 89, issue 12, 1-10

Abstract: Abstract In this paper, we consider a distributed coordination game played by a large number of agents with finite information sets, which characterizes emergence of a single dominant attribute out of a large number of competitors. Formally, N agents play a coordination game repeatedly, which has exactly N pure strategy Nash equilibria, and all of the equilibria are equally preferred by the agents. The problem is to select one equilibrium out of N possible equilibria in the least number of attempts. We propose a number of heuristic rules based on reinforcement learning to solve the coordination problem. We see that the agents self-organize into clusters with varying intensities depending on the heuristic rule applied, although all clusters but one are transitory in most cases. Finally, we characterize a trade-off in terms of the time requirement to achieve a degree of stability in strategies versus the efficiency of such a solution.

Keywords: Statistical; and; Nonlinear; Physics (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1140/epjb/e2016-70464-0

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