Answer Set Planning Under Action Costs

TL;DR

This paper introduces the language Kc, an extension of K with action costs, enabling declarative specification of optimal and admissible plans, and demonstrates its effectiveness through complexity analysis and experimental results.

Contribution

The paper presents Kc, a novel language extending K with action costs, allowing expressive declarative planning for optimality criteria and providing a transformation to answer set programming.

Findings

Kc can express complex planning tasks with costs and optimality criteria.

Transformation to logic programs enables solving planning problems via answer set programming.

Experimental results show promising performance of answer set planning for expressive planning tasks.

Abstract

Recently, planning based on answer set programming has been proposed as an approach towards realizing declarative planning systems. In this paper, we present the language Kc, which extends the declarative planning language K by action costs. Kc provides the notion of admissible and optimal plans, which are plans whose overall action costs are within a given limit resp. minimum over all plans (i.e., cheapest plans). As we demonstrate, this novel language allows for expressing some nontrivial planning tasks in a declarative way. Furthermore, it can be utilized for representing planning problems under other optimality criteria, such as computing ``shortest'' plans (with the least number of steps), and refinement combinations of cheapest and fastest plans. We study complexity aspects of the language Kc and provide a transformation to logic programs, such that planning problems are solved via answer set programming. Furthermore, we report experimental results on selected problems. Our experience is encouraging that answer set planning may be a valuable approach to expressive planning systems in which intricate planning problems can be naturally specified and solved.