Adaptive Coalition Structure Generation

Lucia Cipolina-Kun, Ignacio Carlucho, Kalesha Bullard

Keywords: deep reinforcement learning, coalition formation, social optimum maximization

TL;DR: We introduce a Deep Reinforcement Learning (DRL) framework to form socially-optimal coalitions in an adaptive manner.

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.

Submission Number: 56