Autonomous Swarm Agents Using Case-Based Reasoning

被引：3

作者：

O'Connor, Daniel ^{[1
]}

Kapetanakis, Stelios ^{[2
]}

Samakovitis, Georgios ^{[3
]}

Floyd, Michael ^{[4
]}

Ontanon, Santiago ^{[5
]}

Petridis, Miltos ^{[6
]}

机构：

[1] Univ Oxford, Keble Coll, Oxford, England

[2] Univ Brighton, Sch Comp Engn & Math, Brighton, E Sussex, England

[3] Univ Greenwich, Sch Comp & Math Sci, London, England

[4] Knexus Res Corp, Springfield, VA USA

[5] Drexel Univ, Dept Comp Sci, Philadelphia, PA 19104 USA

[6] Middlesex Univ, Dept Comp, London, England

来源：

ARTIFICIAL INTELLIGENCE XXXV (AI 2018) | 2018年 / 11311卷

关键词：

Case-based reasoning; Swarm Intelligence; Swarm robotics; Multi-agent systems; Real-time strategy; Goal-driven agent; Autonomous computing;

D O I：

10.1007/978-3-030-04191-5_20

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Dynamic planning is a hot topic in autonomous computing. This work presents a novel approach of simulating swarm computing behaviour in a sandbox environment where swarms of robots are challenged to fight against each other with a goal of "conquering" any environment bases. Swarm strategies are being used which are decided, modified and applied at run time. Autonomous swarm agents seem surprisingly applicable to several problems where combined artificial intelligence agents are challenged to generate innovative solutions and evaluate them prior to proposing or adopting the best possible one. This work is applicable in areas where AI agents should make selections close to real time within a range of available options under a multi-constraint, multi-objective mission environment. Relevance to Business Process workflows is also presented and documented.

引用

页码：210 / 216

页数：7

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