分布式约束优化问题及其应用综述
Distributed Constraint Optimization Problems and Applications: A Survey
摘要：
多智能体系统（MAS）是人工智能的一个活跃的研究领域，在工业和其他现实世界的应用中具有越来越重要的影响。在MAS中，自主智能体相互作用以追求个人利益和/或实现共同目标。分布式约束优化问题（Distributed Constraint Optimization Problems，DCOPs）是一种重要的Agent体系结构，它的算法和通信模型都是由具体问题的结构驱动的。在过去的十年中，DCOP模型的几个扩展，使他们能够支持MAS在复杂的，实时的，不确定的环境。本次调查的目的是提供一个概述的DCOP模型，给出了其多个扩展的分类，并解决解决的方法和应用程序，找到一个自然的映射在每一类DCOP。建议的分类DCOP扩展提出了几个未来的观点，并确定了有效的分辨率算法的设计中的挑战，可能通过适应不同领域的战略。
英文摘要：
The field of Multi-Agent System (MAS) is an active area of research within Artificial Intelligence, with an increasingly important impact in industrial and other real-world applications. Within a MAS, autonomous agents interact to pursue personal interests and/or to achieve common objectives. Distributed Constraint Optimization Problems (DCOPs) have emerged as one of the prominent agent architectures to govern the agents' autonomous behavior, where both algorithms and communication models are driven by the structure of the specific problem. During the last decade, several extensions to the DCOP model have enabled them to support MAS in complex, real-time, and uncertain environments. This survey aims at providing an overview of the DCOP model, giving a classification of its multiple extensions and addressing both resolution methods and applications that find a natural mapping within each class of DCOPs. The proposed classification suggests several future perspectives for DCOP extensions, and identifies challenges in the design of efficient resolution algorithms, possibly through the adaptation of strategies from different areas.
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