Adversary Strategy Sampling for Effective Plan Generation

Abstract

Effective plan generation in adversarial environments has to take into account possible actions of adversary agents, i.e., the agent should know what the competitor will likely do. In this paper we propose a novel approach for estimating strategies of the adversary, sampling actions that interfere with the agent's ones. The estimated competitor strategies are used in plan generation by considering that agent's actions have to be applied prior to the ones of the competitor, whose estimated times dictate the agent's deadlines. Missing these deadlines entails additional plan cost.