Towards Run-Time Search for Real-World Multi-Agent Systems

Abigail C. Diller, Erik M. Fredericks
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Abstract

Multi-agent systems (MAS) may encounter uncertainties in the form of unexpected environmental conditions, sub-optimal system configurations, and unplanned interactions between autonomous agents. The number of combinations of such uncertainties may be innumerable, however run-time testing may reduce the issues impacting such a system. We posit that search heuristics can augment a run-time testing process, in-situ, for a MAS. To support our position we discuss our in-progress experimental testbed to realize this goal and highlight challenges we anticipate for this domain.
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面向现实世界多智能体系统的运行时搜索
多智能体系统(MAS)可能会遇到意想不到的环境条件、次优系统配置以及自主智能体之间计划外的交互等形式的不确定性。这种不确定性的组合数量可能是无数的,但是运行时测试可以减少影响这种系统的问题。我们假设搜索启发式可以增加运行时测试过程,在现场,为MAS。为了支持我们的立场,我们讨论了我们正在进行的实验测试平台,以实现这一目标,并强调了我们对该领域的挑战。
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