多主体优化系统
[English version]
* 多主体优化系统 (Multiagent Optimization System, MAOS)，又称多Agent优化系统，或简称MAOS系统.
在MAOS系统中，主体们(Agent)在一个环境(Environment)中进行协作搜索，用来求解能够定义为Landscape (包括一个表达空间和对其中空间状态的质量评估) 的优化问题.
MAOS可用来实现各种算法, 尤其是基于SBIL法则的群集智能和一些计算智能算法的多主体系统实现。
对数值优化问题的求解算法已经包含在SWAF中, 支持粒子群优化算法 (Particle Swarm Optimization, PSO), 差分进化算法 (Differential Evolution, DE), 社会认知优化算法 (Social Cognitive Optimization, SCO), 类电磁机制算法 (Electromagnetism-like Mechanism Heuristic, EM) 等. 另外它的简化版本, 包括 Mini-Swarm系统，已经用于旅行商问题 (Traveling Saleman Problem, TSP), 二次背包问题 (Quadratic Knapsack Problem, QKP), 图着色问题 (Graph Coloring Problem, GCP), Flow-Shop Scheduling Problem (FSP), Quadratic Assignment Problem (QAP) 等组合优化问题.
另外, 它也允许在元行为的基础上实现各种宏行为。一个典型的应用背景为实现各种混合算法, 比如DEPSO混合算法即为DE和PSO的混合.
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Xiao-Feng Xie, Wen-Jun Zhang. SWAF: swarm algorithm framework for numerical optimization. Genetic and Evolutionary Computation Conference (GECCO), LNCS 3102, Seattle, WA, USA, 2004: 238-250. [SpringerLink]
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