Poster
in
Workshop: Agent Learning in Open-Endedness Workshop

Adaptive Coalition Structure Generation

Lucia Cipolina Kun ⋅ Ignacio Carlucho ⋅ Kalesha Bullard

Keywords: Deep Reinforcement Learning coalition formation social optimum maximization

Project Page [ Poster] [ OpenReview]

Abstract

We introduce a Deep Reinforcement Learning (DRL) framework to form socially-optimal coalitions in an adaptive manner. In our approach, agents play a deal-or-no-deal game where each state represents a potential coalition to join. Agents learn to form coalitions that are mutually beneficial, without revealing the coalition value to each other. We conducted an empirical evaluation of our model's generalizability on a ridesharing spatial game.

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