Agent-Based Approach to Continuous Optimisation

被引：1
|
作者：
Byrski, Aleksander [1 ]
Kisiel-Dorohinicki, Marek [1 ]
机构：
[1] AGH Univ Sci & Technol, PL-30059 Krakow, Poland
来源：
MAN-MACHINE INTERACTIONS 3 | 2014年 / 242卷
关键词：
evolutionary algorithms; continuous optimisation; multi-agent computing systems; memetic computation; MULTIAGENT SYSTEMS; GENETIC ALGORITHMS; STOCHASTIC-MODEL; EVOLUTIONARY;
D O I：
10.1007/978-3-319-02309-0_53
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 paper an application of selected agent-based evolutionary computing systems, such as flock-based multi agent system (FLOCK) and evolutionary multi-agent system (EMAS), to the problem of continuous optimisation is presented. Hybridising of agent-based paradigm with evolutionary computation brings a new quality to the meta-heuristic field, easily enhancing individuals with possibilities of perception, interaction with other individuals (agents), adaptation of the search parameters, etc. The experimental examination of selected benchmarks allows to gather the observation regarding the overall efficiency of the systems in comparison to the classical genetic algorithm(as defined by Michalewicz) and memetic versions of all the systems.
引用
收藏
页码：487 / 494
页数：8
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