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| 基于STRIPS的领域知识提取策略 |
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吴向军1, 姜云飞2, 凌应标2
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1.中山大学,软件学院,广东,广州,510275;2.中山大学,信息科学与技术学院,软件研究所,广东,广州,510275
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| 摘要: |
| 提出了谓词之间的一种相似关系,并用该相似关系得到可实现某谓词的动作集.利用该动作集中所有动作的公共前提谓词和公共效果谓词,提取出隐含在动作描述中的领域知识,并给出了描述领域知识的一种形式化方法.最后,对具体的规划问题,可利用领域知识判断出初始状态或目标状态中存在的矛盾.该领域知识的提取策略已应用于智能规划器StepByStep之中,所获取的领域知识对选择待实现的谓词提供了必要的理论依据. |
| 关键词: 人工智能 智能规划 规划领域 STRIPS 相似关系 置换 领域知识 |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.60173039(国家自然科学基金);the Special Foundation of 985 Project of SUN YAT-SEN University of China(中山大学985工程专项资金) |
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| Strategy of Extracting Domain Knowledge for STRIPS World |
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WU Xiang-Jun,JIANG Yun-Fei,LING Ying-Biao
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| Abstract: |
| In this paper, a similarity relation between two predicates is defined first. To a given predicate, the set of action for the predicate can be obtained by the similarity relation. Then, the domain knowledge is extracted from the common fluent in preconditions and effects of all actions for each set of action, and the formalism for the domain knowledge is given. Finally, the contradictions in the initial states and the goal states in a particular planning problem with domain knowledge can be discovered. The strategy of extracting the domain knowledge is integrated in the planner StepByStep, and the domain knowledge is the necessary theory when one predicate by action is realized in the planner. |
| Key words: artificial intelligence AI planning planning domain STRIPS similarity relation substitution domain knowledge |
