Domain Independent Approaches for Finding Diverse Plans

被引:0
|
作者
Srivastava, Biplav [1 ]
Nguyen, Tuan A. [1 ]
Gerevini, Alfonso [1 ]
Kambhampati, Subbarao [1 ]
Do, Minh Binh [1 ]
Serina, Ivan [1 ]
机构
[1] IBM India Res Lab, New Delhi, India
关键词
D O I
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In many planning situations, a planner is required to return a diverse set of plans satisfying the same goals which will be used by the external systems collectively. We take a domain-independent approach to solving this problem. We propose different domain independent distance functions among plans that can provide meaningful insights about the diversity in the plan set. We then describe how two representative state-of-the-art domain independent planning approaches - one based on compilation to CSP, and the other based on heuristic local search - can be adapted to produce diverse plans. We present empirical evidence demonstrating the effectiveness of our approaches.
引用
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页码:2016 / 2022
页数:7
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