Reasoning about Actions in Fuzzy Environment

Reasoning in the presence of imprecision and vagueness is inevitable in many real-world applications including those in robotics and intelligent agents. Although, reasoning about actions is a major component in these real-world applications, current actions languages for reasoning about actions lack the ability to represent and reason about actions in the presence of imprecision and vagueness that stem from effects of actions in these real-world applications. In this paper we present a new action language called fuzzy action language, AF , that allows the representation and reasoning about actions with vague (fuzzy) effects. In addition we define the notions of fuzzy planning and fuzzy plan in the fuzzy action language AF . Furthermore, we describe a fuzzy planner based on the fuzzy action language AF that is developed by translating a fuzzy action theory, FT, in AF into a normal logic program with answer set semantics, Π, where trajectories in FT are equivalent to the answer sets of Π. In addition, we formally prove the correctness of our translation. Furthermore, we show that fuzzy planning problems can be encoded as a SAT problem. Keywords— Answer set programming, fuzzy planning, reasoning about actions with fuzzy effects, reasoning under uncertainty.