Simple local search problems that are hard to solve
SIAM Journal on Computing
On the complexity of cooperative solution concepts
Mathematics of Operations Research
Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
The complexity of pure Nash equilibria
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Bayesian Reinforcement Learning for Coalition Formation under Uncertainty
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Convergence to approximate Nash equilibria in congestion games
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Inapproximability of pure nash equilibria
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Fast convergence to nearly optimal solutions in potential games
Proceedings of the 9th ACM conference on Electronic commerce
The Speed of Convergence in Congestion Games under Best-Response Dynamics
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
On the impact of combinatorial structure on congestion games
Journal of the ACM (JACM)
A fair payoff distribution for myopic rational agents
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Approximating pure nash equilibrium in cut, party affiliation, and satisfiability games
Proceedings of the 11th ACM conference on Electronic commerce
Computing stable outcomes in hedonic games
SAGT'10 Proceedings of the Third international conference on Algorithmic game theory
Computing stable outcomes in hedonic games with voting-based deviations
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
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An important task in the analysis of multiagent systems is to understand how groups of selfish players can form coalitions, i.e., work together in teams. In this paper, we study the dynamics of coalition formation under bounded rationality. We consider settings where each team's profit is given by a concave function, and propose three profit-sharing schemes, each of which is based on the concept of marginal utility. The agents are assumed to be myopic, i.e., they keep changing teams as long as they can increase their payoff by doing so. We study the properties (such as closeness to Nash equilibrium or total profit) of the states that result after a polynomial number of such moves, and prove bounds on the price of anarchy and the price of stability of the corresponding games.