自组织紧急系统的可靠风险感知效率改进

2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems Pub Date : 2011-10-03 DOI:10.1109/SASO.2011.12

Jonathan J. Hudson, J. Denzinger, Holger Kasinger, B. Bauer

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引用次数: 7

摘要

效率改进顾问代理为自组织多代理系统提供咨询服务，以提高运行效率。它识别过去问题中的重复任务，允许为单个代理创建所谓的例外规则，以限制未来的低效行为。存在这样一种危险，即引入的规则可能会损害系统的灵活性，从而损害系统的可靠性。在本文中，我们提出了一个可靠的风险意识效率改进顾问，它使用蒙特卡罗模拟技术进行战略分析，评估预期规则的长期潜力和风险。我们的实验评估，对于动态拾取和交付问题的领域，表明结果是一个最小的，但有效的，一组风险规避例外规则。这些规则可以提供给各个代理，以在保持灵活性的同时可靠地实现整体效率的长期改进。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Dependable Risk-Aware Efficiency Improvement for Self-Organizing Emergent Systems

An efficiency improvement advisor agent acts as a consultation service for a self-organizing multi-agent system that improves operational efficiency. It identifies recurrent tasks in past problems that allow the creation of so-called exception rules for individual agents to limit future inefficient behavior. There exists the danger that introduced rules could possibly infringe on the flexibility and therefore reliability of the system. In this paper, we present a dependable risk-aware efficiency improvement advisor that uses Monte Carlo simulation techniques in strategic analysis assessing the long-term potential and risks of prospective rules. Our experimental evaluation, for the domain of dynamic pickup and delivery problems, shows that the result is a minimal, yet effective, set of risk-averse exception rules. These rules can be provided to individual agents to reliably achieve an overall long-term improvement in efficiency while maintaining flexibility.

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来源期刊

2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems

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