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  • 标题:Answer Set Planning Under Action Costs
  • 本地全文:下载
  • 作者:T. Eiter ; W. Faber ; N. Leone
  • 期刊名称:Journal of Artificial Intelligence Research
  • 印刷版ISSN:1076-9757
  • 出版年度:2003
  • 卷号:19
  • 页码:25-71
  • 出版社:American Association of Artificial
  • 摘要: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.
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