Vidal's library
Title: An Asynchronous Complete Method for General Distributed Constraint Optimization
Author: Pragnesh Jay Modi, Wei-Min Shen, Milind Tambe, and Makoto Yokoo
Book Tittle: Proceedings of Autonomous Agents and Multi-Agent Systems Workshop on Distributed Constraint Reasoning
Pages: 104--118
Year: 2002
Abstract: Distributed constraint optimization requires the optimization of a global objective function that is distributed as a set of valued constraints among a set of autonomous, communicating agents. To date, there does not exist an asynchronous, complete algorithm for general distributed constraint optimization problems. This paper presents Adopt, the first such algorithm that is asynchronous, operates on a general representation, uses linear space and is guaranteed to find optimal solutions. The main idea behind Adopt is a new distributed search strategy that is similar to iterative deepening search and that allows concurrent execution by a set of distributed agents. We show that Adopt outperforms Synchronous Branch and Bound, the only existing optimal algorithm for distributed constraint optimization. Furthermore, in order to isolate whether the speed-ups are due to Adopt s new search strategy or its exploitation of asynchrony, we compare to a synchronous version of iterative deepening, which simulates the centralized iterative deepening search strategy in a distributed environment. We show that the cause of speed-up is partly due to Adopt s new search strategy and partly due to its asynchrony.

Cited by 8  -  Google Scholar

@InProceedings{modi02a,
  author =	 {Pragnesh Jay Modi and Wei-Min Shen and Milind Tambe
                  and Makoto Yokoo},
  title =	 {An Asynchronous Complete Method for General
                  Distributed Constraint Optimization},
  booktitle =	 {Proceedings of Autonomous Agents and Multi-Agent
                  Systems Workshop on Distributed Constraint
                  Reasoning},
  year =	 2002,
  comment =	 {The Adopt algorithm.},
  pages =	 {104--118},
  abstract =	 {Distributed constraint optimization requires the
                  optimization of a global objective function that is
                  distributed as a set of valued constraints among a
                  set of autonomous, communicating agents. To date,
                  there does not exist an asynchronous, complete
                  algorithm for general distributed constraint
                  optimization problems. This paper presents Adopt,
                  the first such algorithm that is asynchronous,
                  operates on a general representation, uses linear
                  space and is guaranteed to find optimal
                  solutions. The main idea behind Adopt is a new
                  distributed search strategy that is similar to
                  iterative deepening search and that allows
                  concurrent execution by a set of distributed
                  agents. We show that Adopt outperforms Synchronous
                  Branch and Bound, the only existing optimal algorithm
                  for distributed constraint
                  optimization. Furthermore, in order to isolate
                  whether the speed-ups are due to Adopt s new search
                  strategy or its exploitation of asynchrony, we
                  compare to a synchronous version of iterative
                  deepening, which simulates the centralized iterative
                  deepening search strategy in a distributed
                  environment. We show that the cause of speed-up is
                  partly due to Adopt s new search strategy and partly
                  due to its asynchrony.},
  keywords =     {multiagent dcop},
  url =		 {http://jmvidal.cse.sc.edu/library/modi02a.pdf},
  googleid = 	 {D62NcyY7DP0J:scholar.google.com/},
  cluster = 	 {18234014027649756431}
}
Last modified: Wed Mar 9 10:15:30 EST 2011