A Conformant Planner with Explicit Disjunctive Representation of Belief States

This paper describes a novel and competitive complete conformant planner. Key to the enhanced performance is an efficient encoding of belief states as disjunctive normal form formulae and an efficient procedure for computing the successor belief state. We provide experimental comparative evaluation on a large pool of benchmarks. The novel design provides great efficiency and enhanced scalability, along with the intuitive structure of disjunctive normal form representations.

• Type: Conference
• Year: 2009
• Where: AIPS
• Authors: Son Thanh To, Enrico Pontelli, Tran Cao Son
• Keywords: AIPS 2009, Artificial Intelligence, Belief State, Disjunctive Normal Form, Normal Form Formulae