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A Deterministic Distributed Algorithm for Reasoning with connected row-convex constraints 16

A Deterministic Distributed Algorithm for Reasoning with Con...

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16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS)

作者： Kong, Shufeng Lee, Jae Hee Li, Sanjiang Univ Technol Sydney Fac Engn & IT Ctr Quantum Software & Informat Sydney NSW Australia

ISBN: (纸本)9781510855076

The class of CRC constraints generalizes several tractable classes of constraints and is expressive enough to model problems in domains such as temporal reasoning, geometric reasoning, and scene labelling. This paper presents the first distributed deterministic algorithm for connected row-convex (CRC) constraints. Our distributed (partial) path consistency algorithm efficiently transforms a CRC constraint network into an equivalent constraint network, where all constraints are minimal (i.e., they are the tightest constraints) and generating all solutions can be done in a backtrackfree manner. When compared with the state-of-the-art distributed algorithm for CRC constraints, which is a randomized one, our algorithm guarantees to generate a solution for satisfiable CRC constraint networks and it is applicable to solve large networks in real distributed systems. The experimental evaluations show that our algorithm outperforms the state-of-the-art algorithm in both practice and theory.

关键词： connected row-convex constraints deterministic algorithm distributed algorithm decomposable network

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A Deterministic Distributed Algorithm for Reasoning with connected row-convex constraints 17

A Deterministic Distributed Algorithm for Reasoning with Con...

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Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems

作者： Shufeng Kong Jae Hee Lee Sanjiang Li University of Technology Sydney Ultimo Australia

The class of CRC constraints generalizes several tractable classes of constraints and is expressive enough to model problems in domains such as temporal reasoning, geometric reasoning, and scene labelling. This paper presents the first distributed deterministic algorithm for connected row-convex (CRC) constraints. Our distributed (partial) path consistency algorithm efficiently transforms a CRC constraint network into an equivalent constraint network, where all constraints are minimal (i.e., they are the tightest constraints) and generating all solutions can be done in a backtrack-free manner. When compared with the state-of-the-art distributed algorithm for CRC constraints, which is a randomized one, our algorithm guarantees to generate a solution for satisfiable CRC constraint networks and it is applicable to solve large networks in real distributed systems. The experimental evaluations show that our algorithm outperforms the state-of-the-art algorithm in both practice and theory.

关键词： decomposable network connected row-convex constraints deterministic algorithm distributed algorithm

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Optimal Algorithms for Min-Closed, Max-Closed and Arc Consistency over connected row convex constraints 17

Optimal Algorithms for Min-Closed, Max-Closed and Arc Consis...

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10th Annual ACM India Compute Conference

作者： Mitra, Shubhadip Dutta, Partha Bhattacharya, Arnab Indian Inst Technol Kanpur Comp Sci & Engn Kanpur Uttar Pradesh India Swiss Re Bengaluru Karnataka India IBM Res Bengaluru India

ISBN: (纸本)9781450353236

A key research interest in the area of Constraint Satisfaction Problems (CSP) is to identify tractable classes of constraints and develop efficient algorithms for solving them. In this paper, we propose an optimal algorithm for solving r-ary min-closed and max-closed constraints. Assuming r = O(1), our algorithm has an optimal running time of O(ct) where c and t are the number of constraints and the maximum size of any constraint, respectively. This significantly improves the existing pairwise consistency based algorithm that takes O(c(2)t(2)) time. Moreover, for (binary) connected row convex (CRC) constraints, we design an optimal algorithm for arc consistency that runs in O(cd) time where d is the largest size of any domain. This again improves upon the existing O(cd(2)) algorithms. This, in turn, leads to a faster algorithm for solving CRC constraints. We also show how our solutions can be applied to determine problems in large distributed IT systems. The experimental evaluation shows that the proposed algorithms are several orders of magnitudes faster than the state-of-the-art algorithms.

关键词： Constraint Satisfaction Problem CSP Min-Closed constraints Max-Closed constraints connected row-convex constraints

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