A number of technical approaches had to be employed within the planner, namely, 1) translating expected reward into a probability of goal satisfaction criterion, 2) monitoring belief states with a Rao-Blackwellized particle, and 3) employing Rao-Blackwellized particles in the McLUG probabilistic conformant planning graph heuristic. POND-Hindsight is an action selection mechanism that evaluates each possible action by generating a number of lookahead samples (up to a xed horizon) that greedily select actions based on their heuristic value and samples the actions' observation; the average goal satisfaction probability of the end horizon belief states is used as the value of each action.