248 research outputs found

    A Bound-Independent Pruning Technique to Speeding up Tree-Based Complete Search Algorithms for Distributed Constraint Optimization Problems

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    Complete search algorithms are important methods for solving Distributed Constraint Optimization Problems (DCOPs), which generally utilize bounds to prune the search space. However, obtaining high-quality lower bounds is quite expensive since it requires each agent to collect more information aside from its local knowledge, which would cause tremendous traffic overheads. Instead of bothering for bounds, we propose a Bound-Independent Pruning (BIP) technique for existing tree-based complete search algorithms, which can independently reduce the search space only by exploiting local knowledge. Specifically, BIP enables each agent to determine a subspace containing the optimal solution only from its local constraints along with running contexts, which can be further exploited by any search strategies. Furthermore, we present an acceptability testing mechanism to tailor existing tree-based complete search algorithms to search the remaining space returned by BIP when they hold inconsistent contexts. Finally, we prove the correctness of our technique and the experimental results show that BIP can significantly speed up state-of-the-art tree-based complete search algorithms on various standard benchmarks

    Observing Non-Gaussian Sources in Heavy-Ion Reactions

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    We examine the possibility of extracting non-Gaussian sources from two-particle correlations in heavy-ion reactions. Non-Gaussian sources have been predicted in a variety of model calculations and may have been seen in various like-meson pair correlations. As a tool for this investigation, we have developed an improved imaging method that relies on a Basis spline expansion of the source functions with an improved implementation of constraints. We examine under what conditions this improved method can distinguish between Gaussian and non-Gaussian sources. Finally, we investigate pion, kaon, and proton sources from the p-Pb reaction at 450 GeV/nucleon and from the S-Pb reaction at 200 GeV/nucleon studied by the NA44 experiment. Both the pion and kaon sources from the S-Pb correlations seem to exhibit a Gaussian core with an extended, non-Gaussian halo. We also find evidence for a scaling of the source widths with particle mass in the sources from the p-Pb reaction.Comment: 16 pages, 15 figures, 5 tables, uses RevTex3.

    HS-CAI: A Hybrid DCOP Algorithm via Combining Search with Context-based Inference

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    Search and inference are two main strategies for optimally solving Distributed Constraint Optimization Problems (DCOPs). Recently, several algorithms were proposed to combine their advantages. Unfortunately, such algorithms only use an approximated inference as a one-shot preprocessing phase to construct the initial lower bounds which lead to inefficient pruning under the limited memory budget. On the other hand, iterative inference algorithms (e.g., MB-DPOP) perform a context-based complete inference for all possible contexts but suffer from tremendous traffic overheads. In this paper, (i)(i) hybridizing search with context-based inference, we propose a complete algorithm for DCOPs, named {HS-CAI} where the inference utilizes the contexts derived from the search process to establish tight lower bounds while the search uses such bounds for efficient pruning and thereby reduces contexts for the inference. Furthermore, (ii)(ii) we introduce a context evaluation mechanism to select the context patterns for the inference to further reduce the overheads incurred by iterative inferences. Finally, (iii)(iii) we prove the correctness of our algorithm and the experimental results demonstrate its superiority over the state-of-the-art

    The smallest eigenvalue of Hankel matrices

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    Let H_N=(s_{n+m}),n,m\le N denote the Hankel matrix of moments of a positive measure with moments of any order. We study the large N behaviour of the smallest eigenvalue lambda_N of H_N. It is proved that lambda_N has exponential decay to zero for any measure with compact support. For general determinate moment problems the decay to 0 of lambda_N can be arbitrarily slow or arbitrarily fast. In the indeterminate case, where lambda_N is known to be bounded below by a positive constant, we prove that the limit of the n'th smallest eigenvalue of H_N for N tending to infinity tends rapidly to infinity with n. The special case of the Stieltjes-Wigert polynomials is discussed

    Incremental DCOP Search Algorithms for Solving Dynamic DCOP Problems

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    Distributed constraint optimization problems (DCOPs) are wellsuited for modeling multi-agent coordination problems. However, most research has focused on developing algorithms for solving static DCOPs. In this paper, we model dynamic DCOPs as sequences of (static) DCOPs with changes from one DCOP to the next one in the sequence. We introduce the ReuseBounds procedure, which can be used by any-space ADOPT and any-space BnB-ADOPT to find cost-minimal solutions for all DCOPs in the sequence faster than by solving each DCOP individually. This procedure allows those agents that are guaranteed to remain unaffected by a change to reuse their lower and upper bounds from the previous DCOP when solving the next one in the sequence. Our experimental results show that the speedup gained from this procedure increases with the amount of memory the agents have available
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