Concept Vector's Semantic Similarity based Capability Planning for Multi-agent Cooperative Systems

被引：2
|
作者：
Li, Shuang [1 ,2 ]
Liu, Wei [1 ,2 ]
Wang, Jing [1 ,2 ]
机构：
[1] Wuhan Inst Technol, Sch Comp Sci Engn, Wuhan, Hubei, Peoples R China
[2] Wuhan Inst Technol, Hubei Prov Key Lab Intelligent Robot, Wuhan, Hubei, Peoples R China
来源：
2017 13TH INTERNATIONAL CONFERENCE ON SEMANTICS, KNOWLEDGE AND GRIDS (SKG 2017) | 2017年
基金：
中国国家自然科学基金;
关键词：
RNCVM; capability compensation planning; commitment;
D O I：
10.1109/SKG.2017.00015
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Self-adaptation of Multi-agent cooperative systems requires dynamic adjustment of agent's decision making at runtime according to the impact of environmental change. Commitment was involved in the capability model in order to express a social relationship between two agents. We present capability compensation planning (CCP) approach and CPA Expansion to achieve capability collaboration and choose available capability or commitment to reach goal. RNCVM based concept vector's semantic similarities of elements is the choose principle for capability planning. The approach in grounded in and illustrated by a case of medical waste transporting.
引用
收藏
页码：38 / 44
页数：7
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