Distributed algorithms for finding centers and medians in networks
ACM Transactions on Programming Languages and Systems (TOPLAS)
Enhancement schemes for constraint processing: backjumping, learning, and cutset decomposition
Artificial Intelligence
Self-stabilization of dynamic systems assuming only read/write atomicity
PODC '90 Proceedings of the ninth annual ACM symposium on Principles of distributed computing
A distributed solution to the network consistency problem
Methodologies for intelligent systems, 5
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
Self-stabilizing systems in spite of distributed control
Communications of the ACM
Graph Algorithms
AND/OR Branch-and-Bound search for combinatorial optimization in graphical models
Artificial Intelligence
Editorial: Introduction: Special Issue on Distributed Constraint Satisfaction
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Asynchronous aggregation and consistency in distributed constraint satisfaction
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Autonomous dynamic reconfiguration in multi-agent systems: improving the quality and efficiency of collaborative problem solving
Co-ordination in artificial agent societies: social structures and its implications for autonomous problem-solving agents
An improved connectionist activation function for energy minimization
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
A graph-based method for improving GSAT
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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This paper characterizes connectionist-type architectures that allow a distributed solution for classes of constraint-satisfaction problems. The main issue addressed is whether there exists a uniform model of computation (where all nodes are indistinguishable) that guarantees convergence to a solution from every initial state of the system, whenever such a solution exists. We show that even for relatively simple constraint networks, such as rings, there is no general solution using a completely uniform, asynchronous, model. However, some restricted topologies like trees can accommodate the uniform, asynchronous, model and a protocol demonstrating this fact is presented. An almost* uniform, asynchronous, network-consistency protocol is also presented. We show that the algorithms are guaranteed to be self-stabilizing, which makes them suitable for dynamic or error-prone environments.