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A Class of Algorithms for Distributed Constraint Optimization
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Multi Agent Systems (MAS) have recently attracted a lot of interest because of their ability to model many real life scenarios where information and control are distributed among a set of different agents. Practical applications include planning, scheduling, distributed control, resource allocation etc. A major challenge in such systems is coordinating agent decisions, such that a globally optimal outcome is achieved. Distributed Constraint Optimization Problems (DCOP) are a framework that recently emerged as one of the most successful approaches to coordination in MAS. "A Class of Algorithms for Distributed Constraint Optimization" addresses three major issues that arise in DCOP: efficient optimization algorithms, dynamic and open environments, and manipulations from self-interested users. It makes significant contributions in all these directions by introducing a series of DCOP algorithms, which are based on dynamic programming and largely outperform previous DCOP algorithms. The basis of this class of algorithms is DPOP, a distributed algorithm that requires only a linear number of messages, thus incurring low networking overhead.
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Subject categories
- Academic > Mathematics > General > Mathematics
- Academic > Computer Science > Computer science
- Academic > Computer Science > Electronic data processing
- Academic > Computer Science > Computer programming
- Academic > Computer Science > Constraint programming
- Academic > Mathematics > Instruments and machines
- Academic > Mathematics > Geometry. Trigonometry.Topology
- Computers > Artificial Intelligence
ISBNs
1607504189
9781586039899
9781607504184