Semiring-based constraint satisfaction and optimization
Journal of the ACM (JACM)
Distributed constraint optimization for medical appointment scheduling
Proceedings of the fifth international conference on Autonomous agents
Communication and Computation in Distributed CSP Algorithms
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Distributed breakout algorithm for distributed constraint optimization problems -- DBArelax
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
Comparing two approaches to dynamic, distributed constraint satisfaction
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Examining DCSP coordination tradeoffs
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Optimal Solution Stability in Dynamic, Distributed Constraint Optimization
IAT '07 Proceedings of the 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology
BnB-ADOPT: an asynchronous branch-and-bound DCOP algorithm
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Evaluating the performance of DCOP algorithms in a real world, dynamic problem
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Journal of Artificial Intelligence Research
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A scalable method for multiagent constraint optimization
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
The distributed breakout algorithms
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Sensor networks and distributed CSP: communication, computation and complexity
Artificial Intelligence - Special issue: Distributed constraint satisfaction
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
PRIMA '09 Proceedings of the 12th International Conference on Principles of Practice in Multi-Agent Systems
A formalization for distributed cooperative sensor resource allocation
KES-AMSTA'08 Proceedings of the 2nd KES International conference on Agent and multi-agent systems: technologies and applications
A constraint based formalisation for distributed cooperative sensor resource allocation
International Journal of Intelligent Information and Database Systems
BnB-ADOPT: an asynchronous branch-and-bound DCOP algorithm
Journal of Artificial Intelligence Research
Incremental DCOP search algorithms for solving dynamic DCOPs
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
SBDO: a new robust approach to dynamic distributed constraint optimisation
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
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Distributed target allocation and tracking is an important research problem. This problem is complex but has many applications in various domains, including, pervasive computing, surveillance and military systems. In this paper we propose a technique to solve the target to sensor allocation problem by modeling the problem as a hierarchical Distributed Constraint Optimization Problem (HDCOP). Distributed Constrain Optimization Problems (DCOPs) tend to be computationally expensive and often intractable, particularly in large problem spaces such as Wireless Sensor Networks (WSNs). To address this challenge we propose changing the sensor to target allocation as a hierarchical set of smaller DCOPs with a shared system of constraints. Thus, we avoid significant computational and communication costs. Furthermore, in contrast to other DCOP modeling methods, a non-binary variable modeling is employed to reduce the number of intra-agent constraints. To evaluate the performance of the proposed approach, we use the surveillance system of the Regional Waterloo Airport as a test case. Two DCOP solution algorithms are considered, namely, the Distributed Breakout Algorithm (DBA) and the Asynchronous Distributed Optimization (ADOPT). We evaluate the computational and communication costs of these two algorithms for solving the target to sensor allocation problem using the proposed hierarchical formulation. We compare the performance of these algorithms with respect to the incurred computational and communication costs.