Promoting Cooperation and Fairness in Self-interested Multi-Agent Systems
Ted Scully, Michael G. Madden
2016
Abstract
The issue of collaboration amongst agents in a multi-agent system (MAS) represents a challenging research problem. In this paper we focus on a form of cooperation known as coalition formation. The problem we consider is how to facilitate the formation of a coalition in a competitive marketplace, where self-interested agents must cooperate by forming a coalition in order to complete a task. Agents must reach a consensus on both the monetary amount to charge for completion of a task as well as the distribution of the required workload. The problem is further complicated because different subtasks have various degrees of difficulty and each agent is uncertain of the payment another agent requires for performing specific subtasks. These complexities, coupled with the self-interested nature of agents, can inhibit or even prevent the formation of coalitions in such a real-world setting. As a solution, an auction-based protocol called ACCORD is proposed. ACCORD manages real-world complexities by promoting the adoption of cooperative behaviour amongst agents. Through extensive empirical analysis we analyse the ACCORD protocol and demonstrate that cooperative and fair behaviour is dominant and any agents deviating from this behaviour perform less well over time.
References
- Aziz, H., Brandt, F., and Seedig, H. (2011). Stable partitions in additively separable hedonic games. Autonomous Agents and Multiagent Systems, 1:183-190.
- Bachrach, Y., Kohli, P., Kolmogorov, V., and Zadimoghaddam, M. (2013). Optimal Coalition Structure Generation in Cooperative Graph Games Finding the Optimal Coalitional Structure. In Twenty-Seventh AAAI Conference on Artificial Intelligence, pages 81-87.
- Dan, W., Cai, Y., Zhou, L., and Wang, J. (2012). A Cooperative Communication Scheme Based on Coalition Formation Game in Clustered Wireless Sensor Networks. IEEE Transactions on Wireless Communications,, 11(3):1190 - 1200.
- Genin, T. and Aknine, S. (2011). Constraining SelfInterested Agents to Guarantee Pareto Optimality in Multiagent Coalition Formation Problem. IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, pages 369-372.
- Ghaffarizadeh, A. and Allan, V. (2013). History Based Coaliton Formation in Hedonic Conext Using Trust. International Journal of Artificial Intelligence & Applications, 4(4):1-8.
- Iwasaki, A., Ueda, S., and Yokoo, M. (2013). Finding the Core for Coalition Structure Utilizing Dual Solution. IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), pages 114-121.
- Rahwan, T. and Ramchurn, S. (2009). An anytime algorithm for optimal coalition structure generation. Journal of Artificial Intelligence, 34:521-567.
- Sandholm, T. and Lesser, V. (1997). Coalitions Among Computationally Bounded Agents. Artificial Intelligence: Special Issue on Economic Principles of MultiAgent Systems, 94:99-137.
- Scully, T. and Madden, M. (2014). Facilitating MultiAgent Coalition Formation through Cooperation in Self-Interested Environments. In Proceedings of European Conference on Multi-Agent Systems. Springer.
- Sen, S. and Dutta, P. (2000). Searching for optimal coalition structures. Proceedings Fourth International Conference on MultiAgent Systems, pages 287-292.
- Shehory, O. (2000). Coalition Formation for Large-Scale Electronic Markets. In Proceedings of the Fourth International Conference on MultiAgent Systems, pages 167-174. IEEE Computer Society.
- Smirnov, A. and Sheremetov, L. (2012). Models of coalition formation among cooperative agents: The current state and prospects of research. Scientific and Technical Information Processing, 39(5):283-292.
- Tos?ic, P. and Ordonez, C. (2012). Distributed protocols for multi-agent coalition formation: a negotiation perspective. Active Media Technology, pages 93-102.
- Tsvetovat, M. and Sycara, K. (2000). Customer Coalitions in the Electronic Marketplace. In Fourth International Conference on Autonomous Agents, pages 263-274.
- Vassileva, J., Breban, S., and Horsch, M. (2002). Agent Reasoning Mechanism for Long-Term Coalitions Based on Decision Making and Trust. Computational Intelligence, 18(4):583-595.
- Wooldridge, M. (2011). Computational aspects of cooperative game theory. Agent and Multi-Agent Systems: Technologies and Applications, 6682.
- Xu, B., Zhang, R., and Yu, J. (2013). Improved Multi-objective Evolutionary Algorithm for Multiagent Coalition Formation. Journal of Software, 8(12):2991-2995.
- Ye, D., Zhang, M., and Sutanto, D. (2013). Self-AdaptationBased Dynamic Coalition Formation in a Distributed Agent Network: A Mechanism and a Brief Survey. Parallel and Distributed Systems, 24(5):1042-1051.
Paper Citation
in Harvard Style
Scully T. and Madden M. (2016). Promoting Cooperation and Fairness in Self-interested Multi-Agent Systems . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-172-4, pages 172-180. DOI: 10.5220/0005754001720180
in Bibtex Style
@conference{icaart16,
author={Ted Scully and Michael G. Madden},
title={Promoting Cooperation and Fairness in Self-interested Multi-Agent Systems},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2016},
pages={172-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005754001720180},
isbn={978-989-758-172-4},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Promoting Cooperation and Fairness in Self-interested Multi-Agent Systems
SN - 978-989-758-172-4
AU - Scully T.
AU - Madden M.
PY - 2016
SP - 172
EP - 180
DO - 10.5220/0005754001720180