Abstract
The interactions among agents in a multi-agent system for coordinating a distributed, problem solving task can be complex, as the distinct sub-problems of the individual agents are interdependent. A distributed protocol provides the necessary framework for specifying these interactions. In a model of interactions where the agents’ social norms are expressed as the message passing behaviours associated with roles, the dependencies among agents can be specified as constraints. The constraints are associated with roles to be adopted by agents as dictated by the protocol. These constraints are commonly handled using a conventional constraint solving system that only allows two satisfactory states to be achieved – completely satisfied or failed. Agent interactions then become brittle as the occurrence of an over-constrained state can cause the interaction between agents to break prematurely, even though the interacting agents could, in principle, reach an agreement. Assuming that the agents are capable of relaxing their individual constraints to reach a common goal, the main issue addressed by this research work is how the agents could communicate and coordinate the constraint relaxation process. The interaction mechanism for this is obtained by reinterpreting a technique borrowed from the constraint satisfaction field (i.e. distributed partial Constraint Satisfaction Problem), deployed and computed at the protocol level.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Decker, K.S., Durfee, E.H., Lesser, V.: Evaluating research in cooperative distributed problem solving, Computer Science Technical Report 88-99, University of Massachusetts at Amherst (1988)
Freuder, E.C., Wallace, R.J.: Partial constraint satisfaction. Artificial Intelligence 58, 21–70 (1992)
Yokoo, M.: Distributed constraint satisfaction: foundations of cooperation in multi-agent systems. Springer, Heidelberg (2001)
Sycara, K.P.: Multiagent systems. AI Magazine 19, 79–92 (1998)
Aldea, A., Lopez, B., Moreno, A., et al.: A multi-agent system for organ transplant coordination. In: Proceedings of the VIII European Conference on AI in Medicine, Carcais, Portugal (2001)
Macho-Gonzales, S., Torrens, M., Faltings, B.: A multi-agent recommender system for planning meetings. In: Proceedings of the Workshop on Agent-based Recommender Systems (WARS 2000), Barcelona, Spain (2000)
Luo, X., Jennings, N.R., Shadbolt, N., et al.: A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments. Artificial Intelligence 148, 53–102 (2003)
Meseguer, P., Bouhmala, N., Bouzoubaa, T., et al.: Current approaches for solving over-constrained problems. Constraints 8, 9–39 (2003)
Hirayama, K., Yokoo, M.: Distributed partial constraint satisfaction problem. In: Proceedings of the Third International Conference on Principles and Practice of Constraint Programming (CP 1997), Linz, Austria (1997)
Faratin, P., Klein, M.: Automated contract negotiation and execution as a system of constraints. In: Proceedings of the Workshop on Distributed Constraint Reasoning, at IJCAI 2001, Seattle, USA (2001)
de Silva, L.P.: Extending agents by transmitting protocols in open systems. RMIT University, Melbourne (2002)
Freire, J., Botelho, L.: Executing explicitly represented protocols. In: Proceedings of the Workshop on Challenges in Open Systems at AAMAS 2002, Bologna, Italy (2002)
McGinnis, J.P.: On the mutability of protocols, in CISA. University of Edinburgh, School of Informatics (2006)
Robertson, D.: A lightweight coordination calculus for agent social norms. In: Proceedings of the Declarative Agent Languages and Technologies at AAMAS 2004, New York, USA (2004)
Esteva, M., Padget, J., Sierra, C.: Formalizing a language for institutions and norms. In: Meyer, J.-J.C., Tambe, M. (eds.) ATAL 2001. LNCS (LNAI), vol. 2333, pp. 348–366. Springer, Heidelberg (2002)
Cabri, G., Ferrari, L., Zambonelli, F.: Role-based approaches for engineering interactions in large-scale multi-agent systems. In: Lucena, C., Garcia, A., Romanovsky, A., Castro, J., Alencar, P.S.C. (eds.) SELMAS 2003. LNCS, vol. 2940, pp. 243–263. Springer, Heidelberg (2004)
SICS, SICStus Prolog User’s Manual. Stockholm: Swedish Institute of Computer Science (SICS) (1999), http://www.sics.se/sicstus.html
Carrieno, N., Gelernter, D.: Linda in context. Communications of the ACM 32, 444–458 (1989)
Modi, P.J., Veloso, M.: Bumping strategies for the multiagent agreement problem. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2005), Utrecht, The Netherlands (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hassan, M.F., Robertson, D. (2008). Constraint Relaxation Approach for Over-Constrained Agent Interaction. In: Ho, TB., Zhou, ZH. (eds) PRICAI 2008: Trends in Artificial Intelligence. PRICAI 2008. Lecture Notes in Computer Science(), vol 5351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89197-0_61
Download citation
DOI: https://doi.org/10.1007/978-3-540-89197-0_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89196-3
Online ISBN: 978-3-540-89197-0
eBook Packages: Computer ScienceComputer Science (R0)