Multi-Context System for Optimization Problems

被引：0
|
作者：
Le, Tiep [1 ]
Tran Cao Son [1 ]
Pontelli, Enrico [1 ]
机构：
[1] New Mexico State Univ, Dept Comp Sci, Las Cruces, NM 88003 USA
来源：
THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | 2019年
关键词：
DISTRIBUTED CONSTRAINT OPTIMIZATION; INCONSISTENCY;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes Multi-context System for Optimization Problems (MCS-OP) by introducing conditional cost-assignment bridge rules to Multi-context Systems (MCS). This novel feature facilitates the definition of a preorder among equilibria, based on the total incurred cost of applied bridge rules. As an application of MCS-OP, the paper describes how MCS-OP can be used in modeling Distributed Constraint Optimization Problems (DCOP), a prominent class of distributed optimization problems that is frequently employed in multi-agent system (MAS) research. The paper shows, by means of an example, that MCS-OP is more expressive than DCOP, and hence, could potentially be useful in modeling distributed optimization problems which cannot be easily dealt with using DCOPs. It also contains a complexity analysis of MCS-OP.
引用
收藏
页码：2929 / 2937
页数：9
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