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Boosting Distributed Constraint Satisfaction
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-540-30201-8_2openalex-snapshot
Constraint Programming Next Challenge: Simplicity of Use
inferredcites →https://doi.org/10.1007/978-3-540-48085-3_16openalex-snapshot
Optimal Distributed Arc-Consistency
inferredcites →https://doi.org/10.1016/j.artint.2004.10.002openalex-snapshot
Asynchronous backtracking without adding links: a new member in the ABT family
inferredcites →https://doi.org/10.1016/s0065-2458(08)60520-3openalex-snapshot
The Algorithm Selection Problem
inferredcites →https://doi.org/10.1109/icdcs.1992.235101openalex-snapshot
Distributed constraint satisfaction for formalizing distributed problem solving
inferredcites →https://doi.org/10.1109/ictai.2001.974446openalex-snapshot
Interleaved backtracking in distributed constraint networks
inferredcites →https://doi.org/10.1142/s0218213002000836openalex-snapshot
INTERLEAVED BACKTRACKING IN DISTRIBUTED CONSTRAINT NETWORKS
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Learning a Mixture of Search Heuristics
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Exceeding the Efficiency of Distributed Approximate Algorithms Enabling by the Multiplexing Method
inferred← citeshttps://doi.org/10.1007/978-3-642-30947-2_36openalex-snapshot
The Optimal Solution Attainment Rate of the Multiplexing Method
inferred← citeshttps://doi.org/10.1007/978-3-642-41482-4_2openalex-snapshot
Boosting Distributed Constraint Networks
inferred← citeshttps://doi.org/10.1007/s10732-010-9134-2openalex-snapshot
Boosting distributed constraint satisfaction
inferred← citeshttps://doi.org/10.1109/ictai.2011.19openalex-snapshot
Dynamic Polarity Adjustment in a Parallel SAT Solver
inferred← citeshttps://doi.org/10.1109/pdmc-hibi.2010.8openalex-snapshot
Parallel SAT solving [Invited paper abstract]
inferred← citeshttps://doi.org/10.1109/snpd.2012.127openalex-snapshot
An Approximate Algorithm for DCOP with Optimal Solution Attainment Rate of 0.99
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Propositional Satisfiability and Constraint Programming
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Seven Challenges in Parallel SAT Solving
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Seven Challenges in Parallel SAT Solving
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A class of algorithms for distributed constraint optimization
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Multi-tier multi-tenant network slicing: A multi-domain games approach
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