Block-Level Goal Recognition Design

被引:0
|
作者
Au, Tsz-Chiu [1 ]
机构
[1] Ulsan Natl Inst Sci & Technol, Dept Comp Sci & Engn, Ulsan, South Korea
来源
THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 18 | 2024年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Existing works on goal recognition design (GRD) consider the underlying domain as a classical planning domain and apply modifications to the domain to minimize the worst case distinctiveness. In this paper, we propose replacing existing modifications with blocks, which group several closely related modifications together such that a block can modify a region in a search space with respect to some design constraints. Moreover, there could be blocks within blocks such that the design space becomes hierarchical for modifications at different levels of granularity. We present 1) a new version of pruned-reduce, a successful pruning rule for GRD, for block-level GRD, and 2) a new pruning rule for pruning some branches in both hierarchical and non-hierarchical design space. Our experiments show that searching in hierarchical design spaces greatly speeds up the redesign process.
引用
收藏
页码:20020 / 20027
页数:8
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