Distributed Multi-Criteria Coordination in Multi-Agent Systems
نویسندگان
چکیده
Distributed constraint optimization (DCOP) has emerged as a key technique for multiagent coordination. Unfortunately, while previous work in DCOP focuses on optimizing a single team objective, domains often require satisfying additional criteria. This paper provides a novel multi-criteria DCOP algorithm, based on two key ideas: (i) transforming multi-criteria problems via virtual variables to harness single-criterion DCOP algorithms; (ii) revealing bounds on criteria to neighbors. These ideas result in interleaved multi-criteria searches, illustrated by modifying Adopt, one of the most efficient DCOP algorithms. Our Multi-Criteria Adopt algorithm (MCA) tailors its performance to whether individual constraints are to be kept private or exploited for efficiency.
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