摘要
将Agent与多Agent系统的相关理论、方法引入到地图多要素协同综合中,分析了Agent技术应用于地图自动综合的优势,设计了基于Agent的要素协同综合概念模型,构建了综合Agent的分类体系,分析了各类综合Agent的知识规则与综合行为,并研究了如何基于知识规则实现自动综合的推理过程,旨在为地图自动综合的全局化、智能化探索一条新途径。
This paper first introduced the multi-Agents theory and methods to map feature coope;ative generalization. The char acteristic of multi-Agent and the advantages of its use in automatic map generalization were analyzed. The conceptual model of cooperative generalization based on multi-Agents was designed. The classification system of generalization Agent was construc- ted. What＇s more,generalization Agent was further broken down into feature-Agent,object-Agent and group-Agent, and struc ture models of these Agents were designed. Different knowledge rules and generalization acts of different Agents were analyzed. The way how to reach reasoning process of automatic generalization based on knowledge rules was researched. Different results could be reached by setting different rules in generalization. However, it needs to be noted that generalization result should be set on powerful knowledge rules. Thus, establishing a powerful map knowledge base and researching self-learning characteristics of the Agents were the key issues in cooperative generalization based nn Agent.
出处
《地理与地理信息科学》
CSCD
北大核心
2013年第6期30-34,共5页
Geography and Geo-Information Science
基金
国家自然科学基金项目(41171350
41301514)
高等学校博士点基金资助项目(20103207110012)
江苏省高校自然科学研究资助项目(13KJB170020)
南通市市级科技创新计划项目(HS2012044)
关键词
地图要素
协同综合
智能体
多智能体系统
map features
cooperative generalization
Agent
multi Agents system
