DATMS: a framework for distributed assumption based reasoning
Distributed artificial intelligence: vol. 2
Efficient local search for very large-scale satisfiability problems
ACM SIGART Bulletin
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
On the run-time behaviour of stochastic local search algorithms for SAT
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Distributed Algorithms
Local search for distributed SAT with complex local problems
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
A Discrete Lagrangian-Based Global-SearchMethod for Solving Satisfiability Problems
Journal of Global Optimization
The Distributed Constraint Satisfaction Problem: Formalization and Algorithms
IEEE Transactions on Knowledge and Data Engineering
The Evolution of Customer Middleware Requirements
PDIS '94 Proceedings of the Third International Conference on Parallel and Distributed Information Systems
Asynchronous Search with Aggregations
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Distributed breakout revisited
Eighteenth national conference on Artificial intelligence
The Effect of Nogood Learning in Distributed Constraint Satisfaction
ICDCS '00 Proceedings of the The 20th International Conference on Distributed Computing Systems ( ICDCS 2000)
Distributed Constraint Satisfaction Algorithm for Complex Local Problems
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
On market-inspired approaches to propositional satisfiability
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
A new method for solving hard satisfiability problems
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
The breakout method for escaping from local minima
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Using CSP look-back techniques to solve real-world SAT instances
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Dynamic prioritization of complex agents in distributed constraint satisfaction problems
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
FGIT '09 Proceedings of the 1st International Conference on Future Generation Information Technology
Distributed constraint satisfaction for urban traffic signal control
KSEM'07 Proceedings of the 2nd international conference on Knowledge science, engineering and management
Solving coarse-grained DisCSPs with local search
Web Intelligence and Agent Systems
Benchmarking hybrid algorithms for distributed constraint optimisation games
Autonomous Agents and Multi-Agent Systems
Logic programming, knowledge representation, and nonmonotonic reasoning
The power of ants in solving Distributed Constraint Satisfaction Problems
Applied Soft Computing
Overlay networks for task allocation and coordination in large-scale networks of cooperative agents
Autonomous Agents and Multi-Agent Systems
The Knowledge Engineering Review
Simple support-based distributed search
AI'06 Proceedings of the 19th international conference on Advances in Artificial Intelligence: Canadian Society for Computational Studies of Intelligence
Target to sensor allocation: A hierarchical dynamic Distributed Constraint Optimization approach
Computer Communications
Hi-index | 0.01 |
We present a new series of distributed constraint satisfaction algorithms, the distributed breakout algorithms, which is inspired by local search algorithms for solving the constraint satisfaction problem (CSP). The basic idea of these algorithms is for agents to repeatedly improve their tentative and flawed sets of assignments for variables simultaneously while communicating such tentative sets with each other until finding a solution to an instance of the distributed constraint satisfaction problem (DisCSP). We introduce four implementations of the distributed breakout algorithms: Single-DB, Multi-DB, Multi-DB^+, and Multi-DB^+^+. Single-DB is a distributed breakout algorithm for solving the DisCSP, where each agent has a single local variable and its related constraints. Multi-DB, on the other hand, is another distributed breakout algorithm for solving the distributed SAT (DisSAT) problem, where each agent has multiple local variables and their related clauses. Multi-DB^+ and Multi-DB^+^+ are stochastic variations of Multi-DB. In Multi-DB^+, we introduce a technique called random break into Multi-DB; in Multi-DB^+^+, we introduce a technique called random walk into Multi-DB^+. We conducted experiments to compare these algorithms with the asynchronous type of distributed constraint satisfaction algorithm. Through these experiments, we found that Single-DB, Multi-DB, and Multi-DB^+ scale up better than the asynchronous type of distributed constraint satisfaction algorithms, but they sometimes show very poor performance. On the other hand, we also found that Multi-DB^+^+, which uses random walk, provides a clear performance improvement.