Distributed snapshots: determining global states of distributed systems
ACM Transactions on Computer Systems (TOCS)
A Distributed Algorithm for Minimum-Weight Spanning Trees
ACM Transactions on Programming Languages and Systems (TOPLAS)
Communicating sequential processes
Communications of the ACM
Constraint-Based Scheduling
Algorithms for Distributed Constraint Satisfaction: A Review
Autonomous Agents and Multi-Agent Systems
Improving Branch and Bound for Jobshop Scheduling with Constraint Propagation
Selected papers from the 8th Franco-Japanese and 4th Franco-Chinese Conference on Combinatorics and Computer Science
Superlinear Speedup in Parallel State-Space Search
Proceedings of the Eighth Conference on Foundations of Software Technology and Theoretical Computer Science
Secure Distributed Constraint Satisfaction: Reaching Agreement without Revealing Private Information
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Constraints-driven scheduling and resource assignment
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Asynchronous Forward-checking for DisCSPs
Constraints
Programming in Scala: A Comprehensive Step-by-step Guide
Programming in Scala: A Comprehensive Step-by-step Guide
Asynchronous forward bounding for distributed COPs
Journal of Artificial Intelligence Research
Distributed CSPs: why it is assumed a variable per agent?
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
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Many combinatorial optimization problems lend themselves to be modeled as distributed constraint optimization problems (DisCOP). Problems such as job shop scheduling have an intuitive matching between agents and machines. In distributed constraint problems, agents control variables and are connected via constraints.We have equipped these agents with a full constraint solver. This makes it possible to use global constraint and advanced search schemes. By empowering the agents with their own solver, we overcome the low performance that often haunts distributed constraint satisfaction problems (DisCSP).By using global constraints, we achieve far greater pruning than traditional DisCSP models. Hence, we dramatically reduce communication between agents. Our experiments show that both global constraints and advanced search schemes are necessary to optimize job shop schedules using DisCSP.