Representing Plans Under Uncertainty

This monograph integrates AI and decision-theoretic approaches to the representation of planning problems by developing a first-order logic of time, chance, and action for representing and reasoning about plans. The semantics of the logic incorporates intuitive properties of time, chance, and action central to the planning problem. The logical language integrates both modal and probabilistic constructs and allows quantification over time points, probability values, and domain individuals. The language can represent the chance that facts hold and events occur at various times and that actions and other events affect the future. An algorithm for the problem of building construction planning is developed and the logic is used to prove the algorithm correct.