一种集成HLA联盟和遗传算法以支持多智能体系统自动设计评估的方法

Sajal K Das, Arthur A Reyes
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引用次数: 14

摘要

我们提出了一种新的设计环境,用于开发多智能体系统(MASs)在移动机器人中的应用。由于紧急行为现象使得几乎不可能直接从规范中合成可行的MAS设计,因此需要进行广泛的模拟研究来评估这些设计。此外,由于MASs系统的设计空间组合较大,候选设计的评估必须以分层、多分辨率、并行和分布式的方式进行。我们提出的设计环境是基于美国国防部的高级体系结构(HLA),这是一个为异构、分布式模拟而建立的软件基础设施。所建议的环境自动生成和管理HLA联合(即分布式和/或并行模拟和服务联合的集合),这些联合通过运行时基础设施(RTI)软件总线进行通信。每个联合为正在开发的MAS模拟不同的候选设计。联合独立且并行地执行。我们提出的设计环境的细化组件使用遗传算法(GA)从当前代中选择最佳候选设计,并生成一组细化的下一代候选设计。为每个下一代设计创建和管理一个联邦,并重复自动设计过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An approach to integrating HLA federations and genetic algorithms to support automatic design evaluation for multi-agent systems

We propose a novel design environment for developing multi-agent systems (MASs) for applications in mobile robotics. Because emergent behavior phenomena make it next to impossible to directly synthesize viable MAS designs from specifications, extensive simulation studies are needed to evaluate these designs. Furthermore, due to the fact that the design space for MASs systems is combinatorially large, the evaluation of candidate designs must be done in a hierarchical, multi-resolution, parallel and distributed manner.

Our proposed design environment is based on US Department of Defense's high-level architecture (HLA), an established software infrastructure for heterogeneous, distributed simulations. The proposed environment automatically generates and manages HLA federations (i.e., collections of distributed and/or parallel simulation and service federates) that communicate over runtime infrastructure (RTI) software buses. Each federation simulates a different candidate design for the MAS under development. Federations execute independently and in parallel. Our proposed design environment's refinement component uses a genetic algorithm (GA) to select the best candidate designs from the current generation and generates a set of refined, next-generation, candidate designs. A federation is created and managed for each of the next-generation designs and the automatic design process is repeated.

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