Declarative Logic-Based Pareto-Optimal Agent Decision Making.

There are many applications where an autonomous agent can perform many sets of actions. It must choose one set of actions based on some behavioral constraints on the agent. Past work has used deontic logic to declaratively express such constraints in logic, and developed the concept of a feasible status set (FSS), a set of actions that satisfy these constraints. However, multiple FSSs may exist and an agent needs to choose one in order to act. As there may be many different objective functions to evaluate status sets, we propose the novel concept of Pareto-optimal FSSs or . We show that checking if a status set is a is co-NP-hard. We develop an algorithm to find a and in special cases when the objective functions are monotonic (or anti-monotonic), we further develop more efficient algorithms. Finally, we conduct experiments to show the efficacy of our approach and we discuss possible ways to handle multiple Pareto-optimal Status Sets.