【24h】

Reducing Accidental Complexity in Planning Problems

机译:减少计划问题中的意外复杂性

获取原文

摘要

Although even propositional STRIPS planning is a hard problem in general, many instances of the problem, including many of those commonly used as benchmarks, are easy. In spite of this, they are often hard to solve for domain-independent planners, because the encoding of the problem into a general problem specification formalism such as STRIPS hides structure that needs to be exploited to solve problems easily. We investigate the use of automatic problem transformations to reduce this "accidental" problem complexity. The main tool is abstraction: we identify a new, weaker, condition under which abstraction is "safe", in the sense that any solution to the abstracted problem can be refined to a concrete solution (in polynomial time, for most cases) and also show how different kinds of problem reformulations can be applied to create greater opportunities for such safe abstraction.
机译:尽管一般来说,即使是提议性的STRIPS计划也很难解决,但该问题的许多实例(包括许多通常用作基准的实例)也很容易。尽管如此,他们通常很难解决与领域无关的计划者的问题,因为将问题编码为一般的问题规范形式,例如STRIPS,隐藏了需要被用来轻松解决问题的结构。我们研究了使用自动问题转换来减少这种“偶然”问题的复杂性。主要工具是抽象:从某种意义上讲,我们可以确定抽象是“安全的”较弱的新条件,从某种意义上讲,可以将抽象问题的任何解决方案提炼为具体的解决方案(在大多数情况下,在多项式时间内),并且展示了如何应用各种不同的问题重构来为此类安全抽象创造更多机会。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号