Vidal's libraryTitle: | The Distributed Constraint Satisfaction Problem: Formalization and Algorithms |
Author: | Makoto Yokoo, Edmund H. Durfee, Toru Ishida, and Kazuhiro Kuwabara |
Journal: | IEEE Transactions on Knowledge and Data Engineering |
Volume: | 10 |
Number: | 5 |
Pages: | 673--685 |
Year: | 1998 |
Abstract: | In this paper, we develop a formalism called a distributed constraint satisfaction problem (distributed CSP) and algorithms for solving distributed CSPs. A distributed CSP is a constraint satisfaction problem in which variables and constraints are distributed among multiple agents. Various application problems in Distributed Artificial Intelligence can be formalized as distributed CSPs. We present our newly developed technique called asynchronous backtracking that allows agents to act asynchronously and concurrently without any global control, while guaranteeing the completeness of the algorithm. Furthermore, we describe how the asynchronous backtracking algorithm can be modified into a more efficient algorithm called an asynchronous weak-commitment search, which can revise a bad decision without exhaustive search by changing the priority order of agents dynamically. The experimental results on various example problems show that the asynchronous weak-commitment search algorithm is, by far more, efficient than the asynchronous backtracking algorithm and can solve fairly large-scale problems. |
Cited by 46 - Google Scholar
@Article{yokoo98a,
author = {Makoto Yokoo and Edmund H. Durfee and Toru Ishida
and Kazuhiro Kuwabara},
title = {The Distributed Constraint Satisfaction Problem:
Formalization and Algorithms},
googleid = {W55Ld-21gRcJ:scholar.google.com/},
journal = {{IEEE} Transactions on Knowledge and Data
Engineering},
year = 1998,
volume = 10,
number = 5,
pages = {673--685},
abstract = {In this paper, we develop a formalism called a
distributed constraint satisfaction problem
(distributed CSP) and algorithms for solving
distributed CSPs. A distributed CSP is a constraint
satisfaction problem in which variables and
constraints are distributed among multiple
agents. Various application problems in Distributed
Artificial Intelligence can be formalized as
distributed CSPs. We present our newly developed
technique called asynchronous backtracking that
allows agents to act asynchronously and concurrently
without any global control, while guaranteeing the
completeness of the algorithm. Furthermore, we
describe how the asynchronous backtracking algorithm
can be modified into a more efficient algorithm
called an asynchronous weak-commitment search, which
can revise a bad decision without exhaustive search
by changing the priority order of agents
dynamically. The experimental results on various
example problems show that the asynchronous
weak-commitment search algorithm is, by far more,
efficient than the asynchronous backtracking
algorithm and can solve fairly large-scale
problems. },
keywords = {multiagent dcsp survey},
url = {http://jmvidal.cse.sc.edu/library/yokoo98a.pdf},
cluster = {3323530956550053993}
}
Last modified: Wed Mar 9 10:14:31 EST 2011