Maintaining Soft Arc Consistency in BnB-ADOPT+ During Search

Gutierrez and Meseguer show how to enforce consistency in BnB-ADOPT + for distributed constraint optimization, but they consider unconditional deletions only. However, during search, more values can be pruned conditionally according to variable instantiations that define subproblems. Enforcing consistency in these subproblems can cause further search space reduction. We introduce efficient methods to maintain soft arc consistencies in every subproblem during search, a non trivial task due to asynchronicity and induced overheads. Experimental results show substantial benefits on three different benchmarks. © 2013 Springer-Verlag.The work of Gutierrez and Meseguer was partially supported by the Spanish project TIN2009-13591-C02-02 and Generalitat de Catalunya 2009-SGR-1434.Peer Reviewe

Enforcing Full Arc Consistency in Asynchronous Forward Bounding Algorithm

The AFB BJ+ DAC* is the latest variant of asynchronous forward bounding algorithms used to solve Distributed Constraint Optimization Problems (DCOPs). It uses Directional Arc Consistency (DAC*) to remove, from domains of a given DCOP, values that do not belong to its optimal solution. However, in some cases, DAC∗ does not remove all suboptimal values, which causes more unnecessary research to reach the optimal solution. In this paper, to clear more and more suboptimal values from a DCOP, we use a higher level of DAC* called Full Directional Arc Consistency (FDAC*). This level is based on reapplying AC* several times, which gives the possibility of making more deletions and thus quickly reaching the optimal solution. Experiments on some benchmarks show that the new algorithm, AFB BJ+ FDAC*, is better in terms of communication load and computation effort

Global constraints in distributed constraint satisfaction and optimization

Global constraints are an essential component in the efficiency of centralized constraint programming. We propose to include global constraints in distributed constraint satisfaction problem (DisCSP) and distributed constraint optimization problem (DCOP). We detail how this inclusion can be done, considering different representations for global constraints (direct, nested, binary). We explore the relation of global constraints with local consistency (both in the hard and soft cases), in particular, for generalized arc consistency (GAC). We provide experimental evidence of the benefits of global constraints on several benchmarks, both for distributed constraint satisfaction and for distributed constraint optimization. © 2013 The Author.2009-SGR-1434; Generalitat de CatalunyaPeer Reviewe

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

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

Prospects for the measurement of muon-neutrino disappearance at the FNAL-Booster

Neutrino physics is nowadays receiving more and more attention as a possible source of information for the long-standing problem of new physics beyond the Standard Model. The recent measurement of the mixing angle $\theta_{13}$ in the standard mixing oscillation scenario encourages us to pursue the still missing results on leptonic CP violation and absolute neutrino masses. However, puzzling measurements exist that deserve an exhaustive evaluation. The NESSiE Collaboration has been setup to undertake conclusive experiments to clarify the muon-neutrino disappearance measurements at small $L/E$, which will be able to put severe constraints to models with more than the three-standard neutrinos, or even to robustly measure the presence of a new kind of neutrino oscillation for the first time. To this aim the use of the current FNAL-Booster neutrino beam for a Short-Baseline experiment has been carefully evaluated. This proposal refers to the use of magnetic spectrometers at two different sites, Near and Far. Their positions have been extensively studied, together with the possible performances of two OPERA-like spectrometers. The proposal is constrained by availability of existing hardware and a time-schedule compatible with the CERN project for a new more performant neutrino beam, which will nicely extend the physics results achievable at the Booster. The possible FNAL experiment will allow to clarify the current $\nu_{\mu}$ disappearance tension with $\nu_e$ appearance and disappearance at the eV mass scale. Instead, a new CERN neutrino beam would allow a further span in the parameter space together with a refined control of systematics and, more relevant, the measurement of the antineutrino sector, by upgrading the spectrometer with detectors currently under R&D study.Comment: 76 pages, 52 figure