@inproceedings{17653,
  author       = {{Polevoy, Gleb and de Weerdt, M.M.}},
  booktitle    = {{Proceedings of the 29th Benelux Conference on Artificial Intelligence}},
  keywords     = {{interaction, reciprocation, contribute, shared effort, curbing, convergence, threshold, Nash equilibrium, social welfare, efficiency, price of anarchy, price of stability}},
  publisher    = {{Springer}},
  title        = {{{Reciprocation Effort Games}}},
  year         = {{2017}},
}

@inproceedings{17654,
  author       = {{Polevoy, Gleb and de Weerdt, M.M.}},
  booktitle    = {{Proceedings of the 29th Benelux Conference on Artificial Intelligence}},
  keywords     = {{agents, projects, contribute, shared effort game, competition, quota, threshold, Nash equilibrium, social welfare, efficiency, price of anarchy, price of stability}},
  publisher    = {{Springer}},
  title        = {{{Competition between Cooperative Projects}}},
  year         = {{2017}},
}

@inproceedings{17659,
  author       = {{Polevoy, Gleb and Trajanovski, Stojan and de Weerdt, Mathijs M.}},
  booktitle    = {{Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems}},
  isbn         = {{978-1-4503-2738-1}},
  keywords     = {{competition, equilibrium, market, models, shared effort games, simulation}},
  pages        = {{861--868}},
  publisher    = {{International Foundation for Autonomous Agents and Multiagent Systems}},
  title        = {{{Nash Equilibria in Shared Effort Games}}},
  year         = {{2014}},
}

@inproceedings{17660,
  author       = {{Polevoy, Gleb and de Weerdt, Mathijs M.}},
  booktitle    = {{Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems}},
  isbn         = {{978-1-4503-2738-1}},
  keywords     = {{dynamics, emotion modeling, negotiation, network interaction, shared effort game}},
  pages        = {{1741--1742}},
  publisher    = {{International Foundation for Autonomous Agents and Multiagent Systems}},
  title        = {{{Improving Human Interaction in Crowdsensing}}},
  year         = {{2014}},
}