Adversarial Planning for Large Multi-agent Simulations

We investigate planning for self-interested agents in large multi-agent simulations. We present two heuristic algorithms that exploit different domain-specific properties in order to find high quality plans with reduced amount of computations. We further suggest finding a formal framework for describing these properties and complementing our previous mostly experimental results by formal guarantees