THE MULTI-AGENT PLANNING PROBLEM

被引：0

作者：

Kalmar-Nagy, Tamas ^{[1
]}

Giardini, Giovanni ^{[2
]}

机构：

[1] Texas A&M Univ, Dept Aerosp Engn, College Stn, TX 77845 USA

[2] Gemelli SpA, Milan, Italy

来源：

ICAART 2011: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1 | 2011年

关键词：

Multiple traveling salesman problem; Genetic algorithm; TRAVELING SALESMAN PROBLEM; GROUPING GENETIC ALGORITHM; RESCUE ROBOTICS; FORMULATIONS;

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：

The purpose of this paper is to present a Multi-Agent planner for a team of autonomous agents. The approach is demonstrated by the Multi-Agent Planning Problem, which is a variant of the classical Multiple Traveling Salesmen Problem (MTSP): given a set of n goals/targets and a team of m agents, the optimal team strategy consists of finding m tours such that each target is visited only once and by only one agent, and the total cost of visiting all nodes is minimal. The proposed solution method is a Genetic Algorithm Inspired Steepest Descent (GAISD) method. To validate the approach, the method has been benchmarked against MTSPs and routing problems. Numerical experiments demonstrate the goodness of the approach.

引用

页码：296 / 305

页数：10

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