Logic Programming for Finding Models in the Logics of Knowledge and its Applications: A Case Study

TL;DR

This paper demonstrates how logic programming can be used to encode and compute models in logics of knowledge, enabling multi-agent planning with complex actions, and presents the first implementation of such a planner.

Contribution

It introduces a novel LP-based approach to model and compute Kripke models for logics of knowledge, supporting multi-agent planning with knowledge and world-altering actions.

Findings

First implementation of a planner for multi-agent knowledge domains

Supports complex multi-agent planning with knowledge and visibility

Enables reasoning about knowledge in multi-agent systems

Abstract

The logics of knowledge are modal logics that have been shown to be effective in representing and reasoning about knowledge in multi-agent domains. Relatively few computational frameworks for dealing with computation of models and useful transformations in logics of knowledge (e.g., to support multi-agent planning with knowledge actions and degrees of visibility) have been proposed. This paper explores the use of logic programming (LP) to encode interesting forms of logics of knowledge and compute Kripke models. The LP modeling is expanded with useful operators on Kripke structures, to support multi-agent planning in the presence of both world-altering and knowledge actions. This results in the first ever implementation of a planner for this type of complex multi-agent domains.