Efficient Open World Reasoning for Planning

TL;DR

This paper introduces PSIPLAN, a knowledge representation scheme enabling efficient, sound, and complete reasoning and planning in open-world scenarios with incomplete knowledge, without explicit possible worlds enumeration.

Contribution

The paper presents PSIPLAN, a novel representation for open-world reasoning that supports polynomial-time state updates and enables a new planning algorithm for quantified goals.

Findings

PSIPLAN allows effective reasoning with incomplete and infinite knowledge.

The state update procedure is polynomial and does not require possible worlds enumeration.

PSIPOP planner handles complex quantified goals with exceptions.

Abstract

We consider the problem of reasoning and planning with incomplete knowledge and deterministic actions. We introduce a knowledge representation scheme called PSIPLAN that can effectively represent incompleteness of an agent's knowledge while allowing for sound, complete and tractable entailment in domains where the set of all objects is either unknown or infinite. We present a procedure for state update resulting from taking an action in PSIPLAN that is correct, complete and has only polynomial complexity. State update is performed without considering the set of all possible worlds corresponding to the knowledge state. As a result, planning with PSIPLAN is done without direct manipulation of possible worlds. PSIPLAN representation underlies the PSIPOP planning algorithm that handles quantified goals with or without exceptions that no other domain independent planner has been shown to achieve. PSIPLAN has been implemented in Common Lisp and used in an application on planning in a collaborative interface.