Coalition, cryptography, and stability: mechanisms for coalition formation in task oriented domains
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Methods for task allocation via agent coalition formation
Artificial Intelligence
Coalition structure generation with worst case guarantees
Artificial Intelligence
Customer coalitions in the electronic marketplace
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Algorithm for combinatorial coalition formation and payoff division in an electronic marketplace
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Generating Coalition Structures with Finite Bound from the Optimal Guarantees
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Overlapping coalition formation for efficient data fusion in multi-sensor networks
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Distributing coalitional value calculations among cooperative agents
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Task allocation via coalition formation among autonomous agents
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A linear approximation method for the Shapley value
Artificial Intelligence
On representing coalitional games with externalities
Proceedings of the 10th ACM conference on Electronic commerce
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
A distributed algorithm for anytime coalition structure generation
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Towards efficient multiagent task allocation in the RoboCup Rescue: a biologically-inspired approach
Autonomous Agents and Multi-Agent Systems
International Journal of Intelligent Information and Database Systems
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
Coalition formation based on marginal contributions and the Markov process
Decision Support Systems
A heuristic approximation method for the Banzhaf index for voting games
Multiagent and Grid Systems
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The process of forming coalitions of software agents generally requires calculating a value for every possible coalition which indicates how beneficial that coalition would be if it was formed. Now, instead of having a single agent calculate all these values (as is typically the case), it is more efficient to distribute this calculation among the agents, thus using all the computational resources available to the system and avoiding the existence of a single point of failure. Given this, we present a novel algorithm for distributing this calculation among agents in cooperative environments. Specifically, by using our algorithm, each agent is assigned some part of the calculation such that the agents' shares are exhaustive and disjoint. Moreover, the algorithm is decentralized, requires no communication between the agents, has minimal memory requirements, and can reflect variations in the computational speeds of the agents. To evaluate the effectiveness of our algorithm, we compare it with the only other algorithm available in the literature for distributing the coalitional value calculations (due to Shehory and Kraus). This shows that for the case of 25 agents, the distribution process of our algorithm took less than 0.02% of the time, the values were calculated using 0.000006% of the memory, the calculation redundancy was reduced from 383229848 to 0, and the total number of bytes sent between the agents dropped from 1146989648 to 0 (note that for larger numbers of agents, these improvements become exponentially better).