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多Agent系统分布式问题求解的代数模型方法(Ⅰ): 社会行为、社会局势和社会动力学
引用本文:帅典勋,顾静.多Agent系统分布式问题求解的代数模型方法(Ⅰ): 社会行为、社会局势和社会动力学[J].计算机学报,2002,25(2):130-137.
作者姓名:帅典勋  顾静
作者单位:1. 华东理工大学计算机科学与工程系,上海,200237,清华大学智能技术与系统国家重点实验室,北京,100080
2. 朗讯科技,中国,有限公司,上海,200230
基金项目:国家自然科学基金重点项目 (60 13 5 0 10 ),国家“九七三”重点基础研究发展规划项目(G19990 3 2 70 7),国家自然科学基金项目 (60 0 73 0 0 8),清华大学智能技术和系统国家重点实验室开放课题基金,高校重点实验室访问学者基金的资助和支持
摘    要:该组论文提出一种新的代数模型方法,用于多Agent系统超分布超并行社会智能问题求解,该方法通过社会动力学和社会智能,统一地处理各种复杂的并行的社会行为,用于求解用常规方法难以处理的许多社会交互问题,本文是组合论文中第一篇,提出多Agent系统分布式问题求解的代数模型结构,讨论多Agent系统中典型社会行为模式及其性质,建立形式化描述,同时也论述了代数模型中的社会局势和社会动力学。

关 键 词:多Agent系统  分布式人工智能  分布式问题求解  社会行为  代数模型  社会局势  社会动力学
修稿时间:2000年1月21日

A New Algebraic Modeling for Distributed Problem-Solving of Multi-Agent Systems(Part Ⅰ): Social Behavior, Social Situation and Social Dynamics
SHUAI Dian Xun , GU Jing.A New Algebraic Modeling for Distributed Problem-Solving of Multi-Agent Systems(Part Ⅰ): Social Behavior, Social Situation and Social Dynamics[J].Chinese Journal of Computers,2002,25(2):130-137.
Authors:SHUAI Dian Xun  GU Jing
Affiliation:SHUAI Dian Xun 1),2) GU Jing 3) 1)
Abstract:Basically, there are two categories in distributed artificial intelligence (DAI): distributed problem solving (DPS) and multi agent system (MAS). DSP is concerned with how to increase the whole outcome of the system through cooperations between individual agents regardless of their personal payoffs. Whereas, in MAS each of autonomous rational individuals tries to increase its own personal utility via social interactions, without some global control strategies and overall consistent knowledge, even without some common general goals. These companion papers are devoted to a new algebraic modeling approach to hyper distributed hyper parallel problem solving in MAS, which is entirely different from the DSP and from other methods currently used in MAS. We try to capture the essential characters of social intelligence associated with complicated concurrent social interactions among individual agents in MAS. The algebraic approach universally deals with social interactions by means of social intelligence and social dynamics, and can be effectively used for such problem solving in MAS that might be difficult to solve in the context of social behaviors by using other conventional methods. This is the first of the companion papers, which addresses the typical social behaviours, their essential characters and their formalization. A conceptual architecture of the algebraic modeling approach to MAS problem solving is given. The social situation and social dynamics of algebraic modeling are also discussed. The simulation on distributed self organized multi task allocations and resource assignments shows the advantages of the algebraic approach in the context of social interactions.
Keywords:multi  agent system    distributed artificial intelligence  distributed problem  solving  social behavior  algebraic modeling
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