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Distributed Forward Checking May Lie for Privacy
, 2007
"... DisFC is an ABTlike algorithm that, instead of sending the value taken by the high priority agent, it sends the domain of the low priority agent that is compatible with that value. With this strategy, plus the use of sequence numbers, some privacy level is achieved. In particular, each agent knows ..."
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DisFC is an ABTlike algorithm that, instead of sending the value taken by the high priority agent, it sends the domain of the low priority agent that is compatible with that value. With this strategy, plus the use of sequence numbers, some privacy level is achieved. In particular, each agent knows its value in the solution, but ignores the values of the others. However, the idea of sending the whole compatible domain each time an agent changes its value may cause a privacy loss on shared constraints that was initially overlooked. To solve this issue, we propose DisFClies, an algorithm that works like DisFC but it may lie about the compatible domains of other agents. It requires a single extra condition: if an agent sends a lie, it has to tell the truth in finite time afterwards. We prove that the algorithm is sound, complete and terminates. We provide experimental results on the increment in privacy achieved, at the extra cost of more search.
ADOPTing: Unifying Asynchronous Distributed Optimization with Asynchronous Backtracking
, 2007
"... This article presents an asynchronous algorithm for solving Distributed Constraint Optimization problems (DCOPs). The proposed technique unifies asynchronous backtracking (ABT) and asynchronous distributed optimization (ADOPT) where valued nogoods enable more flexible reasoning and more opportunitie ..."
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This article presents an asynchronous algorithm for solving Distributed Constraint Optimization problems (DCOPs). The proposed technique unifies asynchronous backtracking (ABT) and asynchronous distributed optimization (ADOPT) where valued nogoods enable more flexible reasoning and more opportunities for communication, leading to an important speedup. While feedback can be sent in ADOPT by COST messages only to one predefined predecessor, our extension allows for sending such information to any relevant agent. The concept of valued nogood is an extension by Dago and Verfaille of the concept of classic nogood that associates the list of conflicting assignments with a cost and, optionally, with a set of references to culprit constraints. DCOPs have been shown to have very elegant distributed solutions, such as ADOPT, distributed asynchronous overlay (DisAO), or DPOP. These algorithms are typically tuned to minimize the longest causal chain of messages as a measure of how the algorithms will scale for systems with remote agents (with large latency in communication). ADOPT has the property of maintaining the initial distribution of the problem. To be efficient, ADOPT needs a preprocessing step consisting of computing a DepthFirst Search (DFS) tree on the constraint graph. Valued nogoods allow for automatically detecting and exploiting the best DFS tree compatible with the current ordering. To exploit such DFS trees it is now sufficient to ensure that they exist. Also, the inference rules available for valued nogoods help to exploit schemes of communication where more feedback is sent to higher priority agents. Together they result in an order of magnitude improvement.
Message delay and asynchronous DisCSP search
, 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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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 shown in experimental studies of asynchronous backtracking algorithms [1, 9]. 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 number of nonconcurrent 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. The performance of two asynchronous search algorithms is measured on randomly generated instances of DisCSPs with delayed messages. The Asynchronous Weak Commitment (AW C) algorithm and Asynchronous Backtracking (ABT). The intrinsic reordering process of AW C dictates a need for a more complex count of nonconcurrent steps of computation. The improved counting algorithm is also needed for Dynamic ordered ABT. The delay of messages is found to have a strong negative effect on AW C and a smaller effect on dynamically ordered ABT.
Boosting distributed constraint satisfaction
 In Int. Conf. on Principles and Practice of Constraint Programming (CP
, 2005
"... Abstract. Competition and cooperation can boost the performance of search. Both can be implemented with a portfolio of algorithms which run in parallel, give hints to each other and compete for being the first to finish and deliver the solution. In this paper we present a new generic framework for t ..."
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Abstract. Competition and cooperation can boost the performance of search. Both can be implemented with a portfolio of algorithms which run in parallel, give hints to each other and compete for being the first to finish and deliver the solution. In this paper we present a new generic framework for the application of algorithms for distributed constraint satisfaction which makes use of both cooperation and competition. This framework improves the performance of two different standard algorithms by one order of magnitude and can reduce the risk of poor performance by up to three orders of magnitude. Moreover it greatly reduces the classical idleness flaw usually observed in distributed hierarchybased searches. We expect our new methods to be similarly beneficial for any treebased distributed search and describe ways on how to incorporate them. 1
NogoodBased Asynchronous ForwardChecking Algorithms
, 2012
"... We propose two new algorithms for solving Distributed Constraint Satisfaction Problems (DisCSPs). The first algorithm, AFCng, is a nogoodbased version of Asynchronous Forward Checking (AFC). Besides its use of nogoods as justification of value removals, AFCng allows simultaneous backtracks going ..."
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We propose two new algorithms for solving Distributed Constraint Satisfaction Problems (DisCSPs). The first algorithm, AFCng, is a nogoodbased version of Asynchronous Forward Checking (AFC). Besides its use of nogoods as justification of value removals, AFCng allows simultaneous backtracks going from different agents to different destinations. The second algorithm, Asynchronous Forward Checking Tree (AFCtree), is based on the AFCng algorithm and is performed on a pseudotree ordering of the constraint graph. AFCtree runs simultaneous search processes in disjoint problem subtrees and exploits the parallelism inherent in the problem. We prove that AFCng and AFCtree only need polynomial space. We compare the performance of these algorithms with other DisCSP algorithms on random DisCSPs and instances from real benchmarks: sensor networks and distributed meeting scheduling. Our experiments show that AFCng improves on AFC and that AFCtree outperforms all compared algorithms, particularly on sparse problems. 1
Asynchronous InterLevel ForwardChecking for
"... Abstract. We propose two new asynchronous algorithms for solving Distributed Constraint Satisfaction Problems (DisCSPs). The first algorithm, AFCng, is a nogoodbased version of Asynchronous Forward Checking (AFC). The second algorithm, Asynchronous InterLevel ForwardChecking (AILFC), is based on ..."
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Abstract. We propose two new asynchronous algorithms for solving Distributed Constraint Satisfaction Problems (DisCSPs). The first algorithm, AFCng, is a nogoodbased version of Asynchronous Forward Checking (AFC). The second algorithm, Asynchronous InterLevel ForwardChecking (AILFC), is based on the AFCng algorithm and is performed on a pseudotree ordering of the constraint graph. AFCng and AILFC only need polynomial space. We compare the performance of these algorithms with other DisCSP algorithms on random DisCSPs in two kinds of communication environments: Fast communication and slow communication. Our experiments show that AFCng improves on AFC and that AILFC outperforms all compared algorithms in communication load. 1
Mindomain retroactive ordering for asynchronous backtracking
, 2008
"... Ordering heuristics are a powerful tool in CSP search algorithms. Among the most successful ordering heuristics are heuristics which enforce a fail first strategy by using the Mindomain property (Haralick and ..."
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Ordering heuristics are a powerful tool in CSP search algorithms. Among the most successful ordering heuristics are heuristics which enforce a fail first strategy by using the Mindomain property (Haralick and
Completeness and Performance of the APO Algorithm
"... Asynchronous Partial Overlay (APO) is a search algorithm that uses cooperative mediation to solve Distributed Constraint Satisfaction Problems (DisCSPs). The algorithm partitions the search into different subproblems of the DisCSP. The original proof of completeness of the APO algorithm is based on ..."
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Asynchronous Partial Overlay (APO) is a search algorithm that uses cooperative mediation to solve Distributed Constraint Satisfaction Problems (DisCSPs). The algorithm partitions the search into different subproblems of the DisCSP. The original proof of completeness of the APO algorithm is based on the growth of the size of the subproblems. The present paper demonstrates that this expected growth of subproblems does not occur in some situations, leading to a termination problem of the algorithm. The problematic parts in the APO algorithm that interfere with its completeness are identified and necessary modifications to the algorithm that fix these problematic parts are given. The resulting version of the algorithm, Complete Asynchronous Partial Overlay (CompAPO), ensures its completeness. Formal proofs for the soundness and completeness of CompAPO are given. A detailed performance evaluation of CompAPO comparing it to other DisCSP algorithms is presented, along with an extensive experimental evaluation of the algorithm’s unique behavior. Additionally, an optimization version of the algorithm, CompOptAPO, is presented, discussed, and evaluated. 1.
Dynamic DFS Tree in ADOPTing
, 2007
"... Several distributed constraint reasoning algorithms employ Depth First Search (DFS) trees on the constraint graph that spans involved agents. In this article we show that it is possible to dynamically detect a minimal DFS tree, compatible with the current order on agents, during the distributed cons ..."
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Several distributed constraint reasoning algorithms employ Depth First Search (DFS) trees on the constraint graph that spans involved agents. In this article we show that it is possible to dynamically detect a minimal DFS tree, compatible with the current order on agents, during the distributed constraint reasoning process of the ADOPT algorithm. This also allows for shorter DFS trees during the initial steps of the algorithm, while some constraints did not yet prove useful given visited combinations of assignments. Earlier distributed algorithms for finding spanning trees on agents did not look to maintain compatibility with an order already used. We also show that announcing a nogood to a single optional agent is bringing significant improvements in the total number of messages. The dynamic detection of the DFS tree brings improvements in simulated time. 1
R.: Scheduling meetings by agents
 In: Proc. 7th Intern. Conf. on Pract. & Theo. Automated Timetabling (PATAT 2008
, 2008
"... The Scheduling of Meetings of multiple users is a real world problem that was studied intensively in recent years. The present paper proposes a realistic model for representing and solving meetings scheduling problems (MSPs) and the use of constraints optimization algorithms to solve MSPs. A central ..."
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The Scheduling of Meetings of multiple users is a real world problem that was studied intensively in recent years. The present paper proposes a realistic model for representing and solving meetings scheduling problems (MSPs) and the use of constraints optimization algorithms to solve MSPs. A central component of the proposed model of MSPs is a mechanism to balance the tradeoff between competitive and cooperative environments. Agents solve the problem by balancing the global (e.g., cooperative) optimum against typical selfinterests of users. These are represented in the model by the quality of the resulting personal schedule. The experimental evaluation of the features of the proposed model uses a Local Search Algorithm which produces a high quality solution in a reasonable time.