On the complexity of cooperative solution concepts
Mathematics of Operations Research
Balanced outcomes in social exchange networks
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Behavioral experiments in networked trade
Proceedings of the 9th ACM conference on Electronic commerce
A behavioral study of bargaining in social networks
Proceedings of the 11th ACM conference on Electronic commerce
The cooperative game theory foundations of network bargaining games
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
Contribution games in social networks
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Local dynamics in bargaining networks via random-turn games
WINE'10 Proceedings of the 6th international conference on Internet and network economics
Fast convergence of natural bargaining dynamics in exchange networks
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Multiagent task allocation in social networks
Autonomous Agents and Multi-Agent Systems
Experiments in social computation
Communications of the ACM
Optimizing social welfare for network bargaining games in the face of unstability, greed and spite
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
Bargaining for revenue shares on tree trading networks
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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We consider models for bargaining in social networks, in which players are represented by vertices and edges represent bilateral opportunities for deals between pairs of players. Each deal yields some fixed wealth if its two players can agree on how to divide it; otherwise it yields no wealth. In such a setting, Chakraborty and Kearns (WINE 2008) introduced a simple axiomatic model that stipulates an equilibrium concept in which all players are rationally satisfied with their shares. We further explore that equilibrium concept here. In particular, we give an FPTAS to compute approximate equilibrium in bipartite graphs. We also show that equilibrium is not unique, and give conditions that ensure uniqueness on regular graphs. Finally, we explore the effect of network structure on solutions given by our model, using simulation methods and statistical analysis.