Finding Diverse High-Quality Plans for Hypothesis Generation

被引：10

作者：

Sohrabi, Shirin ^{[1
]}

Riabov, Anton V. ^{[1
]}

Udrea, Octavian ^{[1
]}

Hassanzadeh, Oktie ^{[1
]}

机构：

[1] IBM Corp, TJ Watson Res Ctr, Yorktown Hts, NY 10598 USA

来源：

ECAI 2016: 22ND EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2016年 / 285卷

关键词：

K SHORTEST PATHS;

D O I：

10.3233/978-1-61499-672-9-1581

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we address the problem of finding diverse high-quality plans motivated by the hypothesis generation problem. To this end, we present a planner called TK* that first efficiently solves the "top-k" cost-optimal planning problem to find k best plans, followed by clustering to produce diverse plans as cluster representatives.

引用

页码：1581 / 1582

页数：2

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