Planning with External Events

I describe a planning methodology for domains with uncertainty in the form of external events that are not completely predictable. The events are represented by enabling conditions and prob­ abilities of occurrence. The planner is goal­ directed and backward chaining, but the subgoals are suggested by analysing the probability of suc­ cess of the partial plan rather than being simply the open conditions of the operators in the plan. The partial plan is represented as a Bayesian be­ lief net to compute its probability of success. Since calculating the probability of success of a plan can be very expensive I introduce two other techniques for computing it, one that uses Monte Carlo simulation to estimate it and one based on a Markov chain representation that uses knowledge about the dependencies between the predicates describing the domain.