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The Distributed Constraint Satisfaction Problem: Formalization and Algorithms
 IEEE Transactions on Knowledge and Data Engineering
, 1998
"... 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 applica ..."
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Cited by 270 (22 self)
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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 weakcommitment 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 weakcommitment search algorithm ...
Distributed Constraint Satisfaction for Formalizing Distributed Problem Solving
, 1992
"... Viewing cooperative distributed problem solving (CDPS) as distributed constraint satisfaction provides a useful formalism for characterizing CDPS techniques. In this paper, we describe this formalism and compare algorithms for solving distributed constraint satisfaction problems (DCSPs). In particul ..."
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Cited by 252 (17 self)
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Viewing cooperative distributed problem solving (CDPS) as distributed constraint satisfaction provides a useful formalism for characterizing CDPS techniques. In this paper, we describe this formalism and compare algorithms for solving distributed constraint satisfaction problems (DCSPs). In particular, we present our newly developed technique called asynchronous backtracking that allows agents to act asynchronously and concurrently, in contrast to the traditional sequential backtracking techniques employed in constraint satisfaction problems. Our experimental results show that solving DCSPs in a distributed fashion is worthwhile when the problems solved by individual agents are looselycoupled. 1 Introduction Cooperative distributed problem solving (CDPS) is a subfield of AI that is concerned with how a set of artificially intelligent agents can work together to solve problems. Recently, [9] has presented the idea of viewing CDPS as a distributed state space search in order to develop...
Adopt: asynchronous distributed constraint optimization with quality guarantees
 ARTIFICIAL INTELLIGENCE LABORATORY, MASSACHUSETTS INSTITUTE OF TECHNOLOGY
, 2005
"... ..."
Algorithms for Distributed Constraint Satisfaction: A Review
 In CP
, 2000
"... . When multiple agents are in a shared environment, there usually exist constraints among the possible actions of these agents. A distributed constraint satisfaction problem (distributed CSP) is a problem to find a consistent combination of actions that satisfies these interagent constraints. Vario ..."
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Cited by 203 (7 self)
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. When multiple agents are in a shared environment, there usually exist constraints among the possible actions of these agents. A distributed constraint satisfaction problem (distributed CSP) is a problem to find a consistent combination of actions that satisfies these interagent constraints. Various application problems in multiagent systems can be formalized as distributed CSPs. This paper gives an overview of the existing research on distributed CSPs. First, we briefly describe the problem formalization and algorithms of normal, centralized CSPs. Then, we show the problem formalization and several MAS application problems of distributed CSPs. Furthermore, we describe a series of algorithms for solving distributed CSPs, i.e., the asynchronous backtracking, the asynchronous weakcommitment search, the distributed breakout, and distributed consistency algorithms. Finally,we showtwo extensions of the basic problem formalization of distributed CSPs, i.e., handling multiple local variables, and dealing with overconstrained problems. Keywords: Constraint Satisfaction, Search, distributed AI 1.
AND/OR Search Spaces for Graphical Models
, 2004
"... The paper introduces an AND/OR search space perspective for graphical models that include probabilistic networks (directed or undirected) and constraint networks. In contrast to the traditional (OR) search space view, the AND/OR search tree displays some of the independencies present in the gr ..."
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Cited by 102 (43 self)
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The paper introduces an AND/OR search space perspective for graphical models that include probabilistic networks (directed or undirected) and constraint networks. In contrast to the traditional (OR) search space view, the AND/OR search tree displays some of the independencies present in the graphical model explicitly and may sometime reduce the search space exponentially. Indeed, most
Distributed Breakout Algorithm for Solving Distributed Constraint Satisfaction Problems
, 1996
"... This paper presents a new algorithm for solving distributed constraint satisfaction problems (distributed CSPs) called the distributedbreakout algorithm, which is inspired by the breakout algorithm for solving centralized CSPs. In this algorithm, each agent tries to optimize its evaluation valu ..."
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Cited by 87 (14 self)
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This paper presents a new algorithm for solving distributed constraint satisfaction problems (distributed CSPs) called the distributedbreakout algorithm, which is inspired by the breakout algorithm for solving centralized CSPs. In this algorithm, each agent tries to optimize its evaluation value (the number of constraint violations) by exchanging its current value and the possible amount of its improvement among neighboring agents. Instead of detecting the fact that agents as a whole are trapped in a localminimum, each agent detects whether it is in a quasilocalminimum, which is a weaker condition than a localminimum, and changes the weights of constraint violations to escape from the quasilocalminimum. Experimental evaluations show this algorithm to be much more efficient than existing algorithms for critically difficult problem instances of distributed graphcoloring problems.
Distributed Constraint Satisfaction Algorithm for Complex Local Problems
, 1998
"... A distributed constraint satisfaction problem can formalize various application problems in MAS, and several algorithms for solving this problem have been developed. One limitation of these algorithms is that they assume each agent has only one local variable. Although simple modifications enable th ..."
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Cited by 70 (9 self)
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A distributed constraint satisfaction problem can formalize various application problems in MAS, and several algorithms for solving this problem have been developed. One limitation of these algorithms is that they assume each agent has only one local variable. Although simple modifications enable these algorithms to handle multiple local variables, obtained algorithms are neither efficient nor scalable to larger problems. We develop a new algorithm that can handle multiple local variables efficiently, which is based on the asynchronous weakcommitment search algorithm. In this algorithm, a bad local solution can be modified without forcing other agents to exhaustively search local problems. Also, the number of interactions among agents can be decreased since agents communicate only when they find local solutions that satisfy all of the local constraints. Experimental evaluations show that this algorithm is far more efficient than an algorithm that uses the prioritization among agents. 1
Analysis of Distributed ArcConsistency Algorithms
, 1997
"... Consistency techniques can significantly reduce the search space of constraint satisfaction problems (CSP). In particular, arcconsistency algorithms, such as AC3 [7], AC4 [8] and AC6 [2], have been designed. In [9], we presented DisAC4, a coarsegrained parallel algorithm designed for distribut ..."
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Cited by 44 (0 self)
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Consistency techniques can significantly reduce the search space of constraint satisfaction problems (CSP). In particular, arcconsistency algorithms, such as AC3 [7], AC4 [8] and AC6 [2], have been designed. In [9], we presented DisAC4, a coarsegrained parallel algorithm designed for distributed memory computer using message passing, which is a distributed version of AC4. We extend here this result. We design DisAC3 and DisAC6. The communication scheme is also extended to allow communication during the propagation step of the consistency algorithms. All these algorithms were systematically experimented. An analysis of the different experiments shows that, as in the sequential case, DisAC6 provides the best performance and that DisAC3 outperforms DisAC4 on most tests. All the distributed algorithms shows a linear speedup. This lead to the conclusion that DisAC6 is a good candidate for distributed arcconsistency.
Mdpop: Faithful distributed implementation of efficient social choice problems
 In AAMASâ€™06  Autonomous Agents and Multiagent Systems
, 2006
"... In the efficient social choice problem, the goal is to assign values, subject to side constraints, to a set of variables to maximize the total utility across a population of agents, where each agent has private information about its utility function. In this paper we model the social choice problem ..."
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Cited by 41 (15 self)
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In the efficient social choice problem, the goal is to assign values, subject to side constraints, to a set of variables to maximize the total utility across a population of agents, where each agent has private information about its utility function. In this paper we model the social choice problem as a distributed constraint optimization problem (DCOP), in which each agent can communicate with other agents that share an interest in one or more variables. Whereas existing DCOP algorithms can be easily manipulated by an agent, either by misreporting private information or deviating from the algorithm, we introduce MDPOP, the first DCOP algorithm that provides a faithful distributed implementation for efficient social choice. This provides a concrete example of how the methods of mechanism design can be unified with those of distributed optimization. Faithfulness ensures that no agent can benefit by unilaterally deviating from any aspect of the protocol, neither informationrevelation, computation, nor communication, and whatever the private information of other agents. We allow for payments by agents to a central bank, which is the only central authority that we require. To achieve faithfulness, we carefully integrate the VickreyClarkeGroves (VCG) mechanism with the DPOP algorithm, such that each agent is only asked to perform computation, report
SelfStabilizing Distributed Constraint Satisfaction
, 1991
"... Distributed architectures and solutions are described for classes of constraint satisfaction problems, called network consistency problems. An inherent assumption of these architectures is that the communication network mimics the structure of the constraint problem. The solutions are required to be ..."
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Cited by 37 (3 self)
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Distributed architectures and solutions are described for classes of constraint satisfaction problems, called network consistency problems. An inherent assumption of these architectures is that the communication network mimics the structure of the constraint problem. The solutions are required to be selfstabilizing and to treat arbitrary networks, which makes them suitable for dynamic or errorprone environments. We first show that even for relatively simple constraint networks, such as rings, there is no selfstabilizing solution that guarantees convergence from every initial state of the system using a completely uniform, asynchronous model (where all processors are identical). An almostuniform, asynchronous, network consistency protocol with one specially designated node is shown and proven correct. We also show that some restricted topologies such as trees can accommodate the uniform, asynchronous model when neighboring nodes cannot take simultaneous steps. 1 Introduction Consid...