面向Agent的信念修正的系统模型

摘要

A belief revision system model for Agent individual was proposed.The definition of resource-bounded Agent and cor-responding belief revision realization method were adopted,which laid a solid foundation for the system’s processing efficiency. Taking advantage of MongoDB’s performance in distributed document-oriented storage and BSON’s universality in data trans-mission,the expandability of system’s storage and the integrity and operation efficiency of belief were improved.For the sake of better regulation for transmitted message between Agents and enhancement of Agent’s compatibility with Web application in data format,ACL’s semantic was integrated with JSON’s grammar to present an Agent communication language JSON-ACL. Experimental results show that the realized system gets good performances on processing relative large-scale belief base.Mo-reover,the module of belief base visualization can reveal the integral structure of different statuses in the form of graph,which provides a description method for belief revision.%提出一种面向 Agent个体的信念修正系统模型。采用资源有限性 Agent的定义及其相应的信念修正实现方法，保证系统的处理效率；利用 MongoDB分布式文档存储的特点和数据存储格式 BSON 在数据传输上的通用性，提高系统在存储方面的可扩展性和信念存储的完整性与操作效率。为更好地规范Agent之间通信数据的格式并增强Agent与Web应用数据传输上的兼容性，整合现有的 Agent 通信语言的语义和 JSON 在数据规范上的特点，提出一种 Agent 通信语言 JSON-ACL。实例验证与分析结果表明，该模型在处理较大信念集的情况时表现良好，为信念修正提供了一种可视化表现形式。