计算机科学 ›› 2011, Vol. 38 ›› Issue (1): 15-19.

• 综述 • 上一篇    下一篇

基于学习的规划技术研究

陈蔼祥,姜云飞,胡桂武,柴啸龙,边芮   

  1. (广东商学院数学与计算科学学院 广州510320);(中山大学软件研究所 广州510275)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(60773201)资助。

Research of Learning-based Planning Techniques

CHEN Ai-xiang,JIANG Yun-fei,HU Gui-wu,CHAI Xiao-long,BIAN Rui   

  • Online:2018-11-16 Published:2018-11-16

摘要: 经过近十多年的努力,现代智能规划器无论是效率还是处理能力均得到了极大提高。鉴于现有规划理论的局限性,进一步提高现有规划技术效率已愈显困难。现有的大多数规划器均不具备学习能力,无法从先前求解经验中学习有用知识。综述了基于学习的规划技术的发展现状,然后重点介绍了规划大赛中最佳学习器所使用的学习技术,最后指出当前基于学习的规划技术研究领域中存在的主要问题。

关键词: 智能规划,基于学习的规划技术,规划器

Abstract: After nearly 10 years of effort, the mordern smart planner, whether its efficiency or processing capacity, all have been greatly enhanced. Subject to the limitations of current planning theory, to further enhance the efficiency of existing planning techniques under current framework has become more difficult Existing planners have not to learn ability, most of them, can not learn from previous experience, useful knowledge to solve. In this paper, we first review the development of planning techniques to learn, and then focused on learning techniques used on the best learning-based planner among international planning competition, concluded the main problems and challenges in current learning technology research of planning.

Key words: Intelligent planning, Learning-based planning technicaues, Smart planner

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