Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal with It

被引:0
作者
Tateo, Davide [1 ]
Banfi, Jacopo [1 ]
Riva, Alessandro [1 ]
Amigoni, Francesco [1 ]
Bonarini, Andrea [1 ]
机构
[1] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, Piazza Leonardo da Vinci 32, Milan, Italy
来源
THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | 2018年
关键词
MULTIROBOT; INTRACTABILITY;
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
In the Multiagent Connected Path Planning problem (MCPP), a team of agents moving in a graph-represented environment must plan a set of start-goal joint paths which ensures global connectivity at each time step, under some communication model. The decision version of this problem asking for the existence of a plan that can be executed in at most a given number of steps is claimed to be NP-complete in the literature. The NP membership proof, however, is not detailed. In this paper, we show that, in fact, even deciding whether a feasible plan exists is a PSPACE-complete problem. Furthermore, we present three algorithms adopting different search paradigms, and we empirically show that they may efficiently obtain a feasible plan, if any exists, in different settings.
引用
收藏
页码:4735 / 4742
页数:8
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