Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
The algorithm design manual
Methods for task allocation via agent coalition formation
Artificial Intelligence
Coalition structure generation with worst case guarantees
Artificial Intelligence
Searching for Optimal Coalition Structures
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
An improved dynamic programming algorithm for coalition structure generation
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Overlapping coalition formation for efficient data fusion in multi-sensor networks
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Anytime optimal coalition structure generation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Near-optimal anytime coalition structure generation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
On representing coalitional games with externalities
Proceedings of the 10th ACM conference on Electronic commerce
Simulated Annealing for Multi-agent Coalition Formation
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
An anytime algorithm for optimal coalition structure generation
Journal of Artificial Intelligence Research
Coalition structure generation in multi-agent systems with positive and negative externalities
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Coalition structure generation utilizing compact characteristic function representations
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Coalition formation with spatial and temporal constraints
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 3 - Volume 3
A distributed algorithm for anytime coalition structure generation
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Anytime dynamic programming for coalition structure generation
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
A Network Flow Approach to Coalitional Games
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Constant factor approximation algorithms for coalition structure generation
Autonomous Agents and Multi-Agent Systems
Computing optimal coalition structures in non-linear logistics domains
International Journal of Intelligent Information and Database Systems
Randomized coalition structure generation
Artificial Intelligence
On coalition formation with sparse synergies
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Coalition structure generation over graphs
Journal of Artificial Intelligence Research
C-link: a hierarchical clustering approach to large-scale near-optimal coalition formation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Coalition formation based on marginal contributions and the Markov process
Decision Support Systems
Fostering Cooperation through Dynamic Coalition Formation and Partner Switching
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Intelligent supervisory control system for home devices using a cyber physical approach
Integrated Computer-Aided Engineering - Anniversary Volume: Celebrating 20 Years of Excellence
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Coalition structure generation involves partitioning a set of agents into exhaustive and disjoint coalitions so as to maximize the social welfare. What makes this such a challenging problem is that the number of possible solutions grows exponentially as the number of agents increases. To date, two main approaches have been developed to solve this problem, each with its own strengths and weaknesses. The state of the art in the first approach is the Improved Dynamic Programming (IDP) algorithm, due to Rahwan and Jennings, that is guaranteed to find an optimal solution in O(3n), but which cannot generate a solution until it has completed its entire execution. The state of the art in the second approach is an anytime algorithm called IP, due to Rahwan et aI., that provides worst-case guarantees on the quality of the best solution found so far, but which is O(nn). In this paper, we develop a novel algorithm that combines both IDP and IP, resulting in a hybrid performance that exploits the strength of both algorithms and, at the same, avoids their main weaknesses. Our approach is also significantly faster (e.g. given 25 agents, it takes only 28% of the time required by IP, and 0.3% of the time required by IDP).