Chaotic iteration for distributed constraint propagation
Proceedings of the 1999 ACM symposium on Applied computing
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Consistency Maintenance for ABT
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
A Dynamic Distributed Constraint Satisfaction Approach to Resource Allocation
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Performance models for large scale multiagent systems: using distributed POMDP building blocks
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Distributed Sensor Networks: A Multiagent Perspective
Distributed Sensor Networks: A Multiagent Perspective
Solving Distributed Constraint Optimization Problems Using Cooperative Mediation
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Impact of problem centralization in distributed constraint optimization algorithms
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Verifying Time and Communication Costs of Rule-Based Reasoners
Model Checking and Artificial Intelligence
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Distributed Constraint Satisfaction Problems (DCSP) is a general framework for multi-agent coordination and conflict resolution. In most DCSP algorithms, inter-agent communication is restricted to only exchanging values of variables, since any additional information-exchange is assumed to lead to significant communication overheads and to a breach of privacy. This paper provides a detailed experimental investigation of the impact of inter-agent exchange of additional legal values among agents, within a collaborative setting. We provide a new run-time model that takes into account the overhead of the additional communication in various computing and networking environments. Our investigation of more than 300 problem settings with the new run-time model (i) shows that DCSP strategies with additional information-exchange can lead to big speedups in a significant range of settings; and (ii) provides categorization of problem settings with big speedups by the DCSP strategies based on extra communication, enabling us to selectively apply the strategies to a given domain. This paper not only provides a useful method for performance measurement to the DCSP community, but also shows the utility of additional communication in DCSP.