Agent能力承诺协作的自适应图规划协议生成算法  

An adaptive graph planning protocol generation algorithm based on agent capability commitment collaboration

作　　者：郭竞知 刘玮[1,2] 徐龙龙 陈灯 GUO Jing-zhi;LIU Wei;XU Long-long;CHEN Deng(School of Computer Science and Engineering,Wuhan Institute of Technology,Wuhan 430073;Hubei Province Key Laboratory of Intelligent Robot,Wuhan 430073,China)

机构地区：[1]武汉工程大学计算机科学与工程学院,湖北武汉430073 [2]智能机器人湖北省重点实验室,湖北武汉430073

出　　处：《计算机工程与科学》2020年第7期1208-1214,共7页Computer Engineering & Science

基　　金：湖北省技术创新专项重大项目(2019AAA045);湖北省自然科学基金(2019CFB172)。

摘　　要：面向开放多智能体系统OMAS的自适应性体现在多Agent通过协作在运行时调整系统行为以适应环境的变化。针对现有多Agent设计时预定义协作机制无法满足运行时自适应协作的问题,提出了一种基于目标-能力-承诺GCC元模型生成自适应多Agent能力承诺协作图规划协议CCGP的算法。首先提出支持上下文环境语义相似度计算的GCC模型;然后将目标与能力(或者承诺)间的语义匹配度引入到基于能力协作的图规划协议中生成优化算法;最后以医疗垃圾AGV运输仿真系统为实验场景进行2组对比实验,实验结果表明CCGP算法对于生成图规划协议的执行时间有明显提高。The adaptability of Open Multi-Agent System(OMAS)is embodied in the adaptation of agents to the changes of environment at runtime by co-adjusting the System behavior.Aiming at the problem that the predefined collaboration mechanism of existing multi-agent design cannot satisfy the runtime adaptive collaboration,this paper proposes an adaptive multi-agent Capability Commitment collaboration Graph-planning Protocol(CCGP)algorithm based on the Goal-Capability-Commitment(GCC)metamodel.Firstly,the GCC model supporting the semantic similarity calculation of context environment is proposed.Secondly,the semantic matching degree between goals and capabilities(or commitments)is introduced into the graph-planning protocol based on capability collaboration to optimize the algorithm.Finally,the medical waste Automated Guided Vehicle transportation system is taken as the experimental scenario to conduct two sets of comparative experiments.The experimental results show that the execution time of CCGP algorithm for graph planning protocol generation algorithm is significantly improved.

关 键 词：GCC模型 能力承诺 自适应协作 语义相似度 图规划 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]