Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Marginal contribution nets: a compact representation scheme for coalitional games
Proceedings of the 6th ACM conference on Electronic commerce
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Overlapping coalition formation for efficient data fusion in multi-sensor networks
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Complexity of constructing solutions in the core based on synergies among coalitions
Artificial Intelligence
Coalition structure generation utilizing compact characteristic function representations
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
A logic-based representation for coalitional games with externalities
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
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Forming effective coalitions is a major research challenge in AI and multi-agent systems. A Coalition Structure Generation (CSG) problem involves partitioning a set of agents into coalitions so that the social surplus is maximized. Ohta et al. introduce an innovative direction for solving CSG, i. e., by representing a characteristic function as a set of rules, a CSG problem can be formalized as the problem of finding a subset of rules that maximizes the sum of rule values under certain constraints. This paper considers two significant extensions of the formalization/algorithm of Ohta et al., i. e., (i) handling negative value rules and (ii) handling externalities among coalitions.