Coalitional Bargaining with Agent Type Uncertainty
Georgios Chalkiadakis, Craig Boutilier
Coalition formation is a problem of great interest in AI, allowing groups of autonomous, individually rational agents to form stable teams. Automating the negotiations underlying coalition formation is, naturally, of special concern. However, research to date in both AI and economics has largely ignored the potential presence of uncertainty in coalitional bargaining. We present a model of discounted coalitional bargaining where agents are uncertain about the types (or capabilities) of potential partners, and hence the value of a coalition. We cast the problem as a Bayesian game in extensive form, and describe its Perfect Bayesian Equilibria as the solutions to a polynomial program. We then present a heuristic algorithm using iterative coalition formation to approximate the optimal solution, and evaluate its performance.