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arXiv · 1412.4166

Binary Log-Linear Learning with Stochastic Communication Links

Arjun Muralidharan·Yuan Yan·Yasamin Mostofi
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Abstract

In this paper, we consider distributed decision-making over stochastic communication links in multi-agent systems. We show how to extend the current literature on potential games with binary log-linear learning (which mainly focuses on ideal communication links) to consider the impact of stochastic communication channels. More specifically, we derive conditions on the probability of link connectivity to achieve a target probability for the set of potential maximizers (in the stationary distribution). Furthermore, our toy example demonstrates a transition phenomenon for achieving any target probability for the set of potential maximizers.

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Arjun Muralidharan, Yuan Yan, Yasamin Mostofi. 2014-12-12. Binary Log-Linear Learning with Stochastic Communication Links. https://arxiv.org/abs/1412.4166

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