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Asynchronous forwardbounding for distributed constraints optimization
 In: Proc. 1st Intern. Workshop on Distributed and Speculative Constraint Processing. (2005
, 2006
"... A new search algorithm for solving distributed constraint optimization problems (DisCOPs) is presented. Agents assign variables sequentially and propagate their assignments asynchronously. The asynchronous forwardbounding algorithm (AFB) is a distributed optimization search algorithm that keeps one ..."
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Cited by 47 (8 self)
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A new search algorithm for solving distributed constraint optimization problems (DisCOPs) is presented. Agents assign variables sequentially and propagate their assignments asynchronously. The asynchronous forwardbounding algorithm (AFB) is a distributed optimization search algorithm that keeps one consistent partial assignment at all times. Forward bounding propagates the bounds on the cost of solutions by sending copies of the partial assignment to all unassigned agents concurrently. The algorithm is described in detail and its correctness proven. Experimental evaluation of AFB on random MaxDisCSPs reveals a phase transition as the tightness of the problem increases. This effect is analogous to the phase transition of MaxCSP when local consistency maintenance is applied [3]. AFB outperforms Synchronous Branch & Bound (SBB) as well as the asynchronous stateoftheart ADOPT algorithm, for the harder problem instances. Both asynchronous algorithms outperform SBB by a large factor. 1
Open constraint programming
 Artifitial Intelligence
"... Constraint satisfaction and optimization problems often involve multiple participants. For example, producing an automobile involves a supply chain of many companies. Scheduling production, delivery and assembly of the different parts would best be solved as a constraint optimization problem ([35]). ..."
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Cited by 38 (5 self)
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Constraint satisfaction and optimization problems often involve multiple participants. For example, producing an automobile involves a supply chain of many companies. Scheduling production, delivery and assembly of the different parts would best be solved as a constraint optimization problem ([35]). A more familiar task for most of us is meeting scheduling: arrange a set of meetings with varying participants such that no two meetings involving the same person are scheduled at the same time, while respecting order and deadline constraints ([18, 22]). Another application that has been studied in detail is coordinating a network of distributed sensors ([2]). Such problems can of course be solved by gathering all constraints and optimization criteria into a single large CSP, and then solving this problem using a centralized algorithm. In practice there are many cases where this is not feasible, because it is impossible to bound the problem to a manageable set of variables. For example, in meeting scheduling, once two people are planning a common meeting, this meeting is potentially in conflict with many other meetings either of them are planning and whose times are decided in parallel. A centralized solver does not know beforehand
Message delay and DisCSP search algorithms
 ANN MATH ARTIF INTELL (2006 ) 46 : 415–439
, 2006
"... Distributed constraint satisfaction problems (DisCSPs) are composed of agents, each holding its own variables, that are connected by constraints to variables of other agents. Due to the distributed nature of the problem, message delay can have unexpected effects on the behavior of distributed searc ..."
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Cited by 32 (18 self)
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Distributed constraint satisfaction problems (DisCSPs) are composed of agents, each holding its own variables, that are connected by constraints to variables of other agents. Due to the distributed nature of the problem, message delay can have unexpected effects on the behavior of distributed search algorithms on DisCSPs. This has been recently shown in experimental studies of asynchronous backtracking algorithms (Bejar et al., Artif. Intell., 161:117–148, 2005; Silaghi and Faltings, Artif. Intell., 161:25–54, 2005). To evaluate the impact of message delay on the run of DisCSP search algorithms, a model for distributed performance measures is presented. The model counts the number of non concurrent constraints checks, to arrive at a solution, as a non concurrent measure of distributed computation. A simpler version measures distributed computation cost by the nonconcurrent number of steps of computation. An algorithm for computing these distributed measures of computational effort is described. The realization of the model for measuring performance of distributed search algorithms is a simulator which includes the cost of message delays. Two families of distributed search algorithms on DisCSPs are investigated. Algorithms that run a single search process, and multiple search processes algorithms. The two families of algorithms are described and associated with existing algorithms. The performance of three representative algorithms of these two families is measured on randomly generated instances of DisCSPs with delayed messages. The delay of messages is found to have a strong negative effect on single search process algorithms, whether synchronous or asynchronous. Multi
Dynamic Ordering for Asynchronous Backtracking on DisCSPs
, 2006
"... An algorithm that performs asynchronous backtracking on distributed CSPs, with dynamic ordering of agents is proposed, ABT DO. Agents propose reorderings of lower priority agents and send these proposals whenever they send assignment messages. Changes of ordering triggers a different computation of ..."
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Cited by 30 (8 self)
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An algorithm that performs asynchronous backtracking on distributed CSPs, with dynamic ordering of agents is proposed, ABT DO. Agents propose reorderings of lower priority agents and send these proposals whenever they send assignment messages. Changes of ordering triggers a different computation of Nogoods. The dynamic ordered asynchronous backtracking algorithm uses polynomial space, similarly to standard ABT. TheABT DO algorithm with three different ordering heuristics is compared to standard ABT on randomly generated DisCSPs. A Nogoodtriggered heuristic, inspired by dynamic backtracking, is found to outperform static order ABT by a large factor in runtime and improve the network load.
Asynchronous Forwardchecking for DisCSPs
, 2007
"... A new search algorithm for solving distributed constraint satisfaction problems (DisCSPs) is presented. Agents assign variables sequentially, but perform forward checking asynchronously. The asynchronous forwardchecking algorithm (AFC) is a distributed search algorithm that keeps one consistent par ..."
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Cited by 21 (3 self)
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A new search algorithm for solving distributed constraint satisfaction problems (DisCSPs) is presented. Agents assign variables sequentially, but perform forward checking asynchronously. The asynchronous forwardchecking algorithm (AFC) is a distributed search algorithm that keeps one consistent partial assignment at all times. Forward checking is performed by sending copies of the partial assignment to all unassigned agents concurrently. The algorithm is described in detail and its correctness proven. The sequential assignment method of AFC leads naturally to dynamic ordering of agents during search. Several ordering heuristics are presented. The three best heuristics are evaluated and shown to improve the performance of AFC with static order by a large factor. An experimental comparison of AFC to asynchronous backtracking (ABT) on randomly generated DisCSPs is also presented. AFC with ordering heuristics outperforms ABT by a large factor on the harder instances of random DisCSPs. These results hold for two measures of performance: number of nonconcurrent constraints checks and number of messages sent.
DisChoco: A platform for distributed constraint programming
"... Abstract. Opensource platforms are very useful for development and experimentation in constraint programming. However, until recently, no such platform existed for distributed constraint programming. This paper presents DisChoco, a platform for distributed constraint programming. DisChoco is a Java ..."
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Cited by 17 (5 self)
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Abstract. Opensource platforms are very useful for development and experimentation in constraint programming. However, until recently, no such platform existed for distributed constraint programming. This paper presents DisChoco, a platform for distributed constraint programming. DisChoco is a Java library implemented using the Choco solver and simple agent communication infrastructure (SACI). DisChoco can be used for simulation of a multiagents environment on a single Java virtual machine, or performed in an environment physically distributed for a realistic use. DisChoco takes into account agent with a complex local problem, message loss, message corruption, and message delay. The implementation of DisChoco was made to offer a modular software architecture which accepts extensions easily. This paper presents the software architecture and illustrates how to implement a specific protocol. 1
Concurrent search for distributed CSPs
 Artificial Intelligence
, 2006
"... A distributed concurrent search algorithm for distributed constraint satisfaction problems (DisCSPs) is presented. Concurrent search algorithms are composed of multiple search processes (SPs) that operate concurrently and scan nonintersecting parts of the global search space. Each SP is represente ..."
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Cited by 10 (4 self)
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A distributed concurrent search algorithm for distributed constraint satisfaction problems (DisCSPs) is presented. Concurrent search algorithms are composed of multiple search processes (SPs) that operate concurrently and scan nonintersecting parts of the global search space. Each SP is represented by a unique data structure, containing a current partial assignment (CPA), that is circulated among the different agents. Search processes are generated dynamically, started by the initializing agent, and by any number of agents during search. In the proposed, ConcDB, algorithm, all search processes perform dynamic backtracking. As a consequence of backjumping, a search space can be found unsolvable by a different search process. This enhances the efficiency of the ConcDB algorithm. Concurrent Dynamic Backtracking is an asynchronous distributed algorithm and is shown to be faster than former algorithms for solving DisCSPs. Experimental evaluation of ConcDB, on randomly generated DisCSPs demonstrates that the network load of ConcDB is similar to the network load of synchronous backtracking and is much lower than that of asynchronous backtracking. The advantage of Concurrent Search is more pronounced in the presence of imperfect communication, when messages are randomly delayed. Key Words: Constraints Satisfaction, Search, Distributed AI. 1.
Generalized Dynamic Ordering for Asynchronous Backtracking On Discsps
"... Dynamic reordering of variables is known to be very important for solving constraint satisfaction problems (CSPs). Many attempts were made to apply this principle for improving ..."
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Cited by 9 (0 self)
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Dynamic reordering of variables is known to be very important for solving constraint satisfaction problems (CSPs). Many attempts were made to apply this principle for improving
Connecting ABT with arc consistency
 IN: CP
"... ABT is the reference algorithm for asynchronous distributed constraint satisfaction. When searching, ABT produces nogoods as justifications of deleted values. When one of such nogoods has an empty lefthand side, the considered value is eliminated unconditionally, once and for all. This value dele ..."
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Cited by 8 (6 self)
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ABT is the reference algorithm for asynchronous distributed constraint satisfaction. When searching, ABT produces nogoods as justifications of deleted values. When one of such nogoods has an empty lefthand side, the considered value is eliminated unconditionally, once and for all. This value deletion can be propagated using standard arc consistency techniques, producing new deletions in the domains of other variables. This causes substantial reductions in the search effort required to solve a class of problems. We also extend this idea to the propagation of conditional deletions, something already proposed in the past. We provide experimental results that show the benefits of the proposed approach, especially considering communication cost.
Secure discsp protocols  from centralized towards distributed solutions
 in DCR05 Workshop
, 2005
"... Abstract. We present new protocols for secure distributed constraint satisfaction problems (DisCSPs). The presented protocols are the first to enable an oblivious use of advanced search techniques heuristics. The first protocol is a centralized protocol, where two of the agents collect ‘encrypted’ d ..."
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Cited by 7 (0 self)
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Abstract. We present new protocols for secure distributed constraint satisfaction problems (DisCSPs). The presented protocols are the first to enable an oblivious use of advanced search techniques heuristics. The first protocol is a centralized protocol, where two of the agents collect ‘encrypted’ data from all other parties, and obliviously perform a search algorithm. Our protocol improves on the previous solution of [YKH05] in several ways: It does not require introducing new agents into the protocol; it enables the use of nontrivial search techniques such as backjumping and ordering heuristics of variables and values; and, it completely eliminates information leakage to all agents. Our second protocol makes the first steps toward a feasible distributed secured protocol for solving DisCSPs. Our protocol enables agents to concurrently perform non sequential (asynchronous) algorithms. It forms an alternative network, whose nodes are small groups (e.g. pairs) of agents, that is generated from the original DisCSP. Each node group obliviously performs the roles of all its members in the search algorithm. We also identify the communication pattern of the protocol as a possible leakage source, and suggest how to eliminate this leakage. Finally, we discuss a hybrid solution that combines the centralized and distributed protocols and reduces the total communication cost. 1