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Computing Coalitions in Multiagent Systems: A Contextual Reasoning Approach

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8953))

Abstract

In multiagent systems, agents often have to rely on other agents to reach their goals, for example when they lack a needed resource or do not have the capability to perform a required action. Agents therefore need to cooperate. Some of the questions then raised, such as, which agent to cooperate with, are addressed in the field of coalition formation. In this paper we go further and first, address the question of how to compute the solution space for the formation of coalitions using a contextual reasoning approach. We model agents as contexts in Multi-Context Systems (MCS) and dependence relations among agents as bridge rules. We then systematically compute all potential coalitions using algorithms for MCS equilibria. Finally, given a set of functional and non-functional requirements, we propose ways to select the best solutions. We illustrate our approach with an example from robotics.

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Notes

  1. 1.

    http://www.kr.tuwien.ac.at/research/systems/dmcs/.

  2. 2.

    http://www.kr.tuwien.ac.at/research/systems/mcsie/.

References

  1. Antoniou, G., Papatheodorou, C., Bikakis, A.: Reasoning about context in ambient intelligence environments: a report from the field. In: Principles of Knowledge Representation and Reasoning: Proceedings of the 12th International Conference, KR 2010, Toronto, Ontario, Canada, 9–13 May 2010, pp. 557–559. AAAI Press (2010)

    Google Scholar 

  2. Bikakis, A., Antoniou, G., Hassapis, P.: Strategies for contextual reasoning with conflicts in ambient intelligence. Knowl. Inf. Syst. 27(1), 45–84 (2011)

    Article  Google Scholar 

  3. Boella, G., Sauro, L., van der Torre, L.: Algorithms for finding coalitions exploiting a new reciprocity condition. Logic J. IGPL 17(3), 273–297 (2009)

    Article  MATH  Google Scholar 

  4. Borgida, A., Serafini, L.: Distributed description logics: assimilating information from peer sources. J. Data Semant. 1, 153–184 (2003)

    Google Scholar 

  5. Bouquet, P., Giunchiglia, F., van Harmelen, F., Serafini, L., Stuckenschmidt, H.: C-OWL: contextualizing ontologies. In: Fensel, D., Sycara, K., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 164–179. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  6. Brewka, G., Eiter, T.: Equilibria in heterogeneous nonmonotonic multi-context systems. In: Proceedings of the 22nd AAAI Conference on Artificial Intelligence, July 22–26 2007, Vancouver, British Columbia, Canada, pp. 385–390 (2007)

    Google Scholar 

  7. Caire, P., Villata, S., Boella, G., van der Torre, L.: Conviviality masks in multiagent systems. In: 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, 12–16 May 2008, vol. 3, pp. 1265–1268 (2008)

    Google Scholar 

  8. Caire, P., Alcade, B., van der Torre, L., Sombattheera, C.: Conviviality measures. In: 10th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Taipei, Taiwan, 2–6 May 2011 (2011)

    Google Scholar 

  9. Caire, P., Bikakis, A., Le Traon, Y.: Information dependencies in MCS: Conviviality-based model and metrics. In: Boella, G., Elkind, E., Savarimuthu, B.T.R., Dignum, F., Purvis, M.K. (eds.) PRIMA 2013. LNCS, vol. 8291, pp. 405–412. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  10. Dao-Tran, M., Eiter, T., Fink, M., Krennwallner, T.: Dynamic distributed nonmonotonic multi-context systems. Nonmonotonic Reasoning, Essays Celebrating its 30th Anniversary, Studies in Logic 31

    Google Scholar 

  11. Dao-Tran, M., Eiter, T., Fink, M., Krennwallner, T.: Distributed nonmonotonic multi-context systems. In: Principles of Knowledge Representation and Reasoning: Proceedings of the Twelfth International Conference, KR 2010, Toronto, Ontario, Canada, 9–13 May 2010 (2010)

    Google Scholar 

  12. Eiter, T., Fink, M., Schüller, P., Weinzierl, A.: Finding explanations of inconsistency in multi-context systems. In: Principles of Knowledge Representation and Reasoning: Proceedings of the Twelfth International Conference, KR 2010, Toronto, Ontario, Canada, 9–13 May 2010. AAAI Press (2010)

    Google Scholar 

  13. Eiter, T., Fink, M., Weinzierl, A.: Preference-based inconsistency assessment in multi-context systems. In: Janhunen, T., Niemelä, I. (eds.) JELIA 2010. LNCS, vol. 6341, pp. 143–155. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  14. Gerkey, B.P., Matarić, M.J.: Sold!: auction methods for multi-robot coordination. IEEE Trans. Robot. Autom. Spec. Issue Multi-Robot Syst. 18(5), 758–768 (2002). http://robotics.usc.edu/publications/10/ (Also Technical report IRIS-01-399)

    Article  Google Scholar 

  15. Ghidini, C., Giunchiglia, F.: Local models semantics, or contextual reasoning = locality + compatibility. Artif. Intell. 127(2), 221–259 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  16. Giunchiglia, F., Serafini, L.: Multilanguage hierarchical logics, or: how we can do without modal logics. Artif. Intell. 65(1), 29–70 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  17. Grossi, D., Turrini, P.: Dependence theory via game theory. In: van der Hoek, W., Kaminka, G.A., Lespérance, Y., Luck, M., Sen, S. (eds.) AAMAS, pp. 1147–1154. IFAAMAS (2010)

    Google Scholar 

  18. Klusch, M., Gerber, A.: Dynamic coalition formation among rational agents. IEEE Intell. Syst. 17(3), 42–47 (2002)

    Article  Google Scholar 

  19. Kronbak, L.G., Lindroos, M.: Sharing rules and stability in coalition games with externalities. Mar. Resour. Econ. 22, 137–154 (2007)

    Google Scholar 

  20. Lemaire, T., Alami, R., Lacroix, S.: A distributed tasks allocation scheme in multi-uav context. In: Proceedings of the 2004 IEEE International Conference on Robotics and Automation, ICRA 2004, April 26 - May 1 2004, New Orleans, LA, USA, pp. 3622–3627 (2004)

    Google Scholar 

  21. Lenat, D.B., Guha, R.V.: Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project. Addison-Wesley Longman Publishing Co., Inc., Boston (1989)

    Google Scholar 

  22. Liemhetcharat, S., Veloso, M.M.: Weighted synergy graphs for effective team formation with heterogeneous ad hoc agents. Artif. Intell. 208, 41–65 (2014)

    Article  MathSciNet  Google Scholar 

  23. Mesterton-Gibbons, M.: An Introduction to Game-Theoretic Modelling. Addison-Wesley, Redwood (1992)

    MATH  Google Scholar 

  24. O’Sullivan, A., Sheffrin, S.M.: Economics: Principles in Action. Pearson Prentice Hall, Needham (2006)

    Google Scholar 

  25. Parsons, S., Sierra, C., Jennings, N.R.: Agents that reason and negotiate by arguing. J. Logic Comput. 8(3), 261–292 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  26. Sabater, J., Sierra, C., Parsons, S., Jennings, N.R.: Engineering executable agents using multi-context systems. J. Logic Comput. 12(3), 413–442 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  27. Sauro, L.: Formalizing Admissibility Criteria in Coalition Formation among Goal Directed Agents. Ph.D. thesis, University of Turin, Italy (2006)

    Google Scholar 

  28. Schmeidler, D.: The nucleolus of a characteristic functional game. SIAM J. Appl. Math. 17, 1163–1170 (1969)

    Article  MATH  MathSciNet  Google Scholar 

  29. Shapley, L.S.: A value for n-person games. Ann. Math. Stud. 28, 307–317 (1953)

    MathSciNet  Google Scholar 

  30. Shehory, O., Kraus, S.: Methods for task allocation via agent coalition formation. Artif. Intell. 101(1–2), 165–200 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  31. Sichman, J.S.: Depint: dependence-based coalition formation in an open multi-agent scenario. J. Artif. Soc. Soc. Simul. 1(2) (1998)

    Google Scholar 

  32. Sichman, J.S., Conte, R.: Multi-agent dependence by dependence graphs. In: Proceedings of The First International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2002, pp. 483–490. ACM (2002)

    Google Scholar 

  33. Sichman, J.S., Conte, R., Castelfranchi, C., Demazeau, Y.: A social reasoning mechanism based on dependence networks. In: Proceedings of the Eleventh European Conference on Artificial Intelligence, Amsterdam, The Netherlands, 8–12 August 1994, pp. 188–192 (1994)

    Google Scholar 

  34. Sichman, J.S., Demazeau, Y.: On social reasoning in multi-agent systems. Revista Iberoamericana de Inteligencia Artificial 13, 68–84 (2001)

    Google Scholar 

  35. Tang, F., Parker, L.E.: Asymtre: automated synthesis of multi-robot task solutions through software reconfiguration. In: Proceedings of the 2004 IEEE International Conference on Robotics and Automation, ICRA 2004, April 26 - May 1 2004, New Orleans, LA, USA, pp. 1501–1508 (2005)

    Google Scholar 

  36. Zhang, Y., Parker, L.E.: Iq-asymtre: forming executable coalitions for tightly coupled multirobot tasks. IEEE Trans. Robot. 29(2), 400–416 (2013)

    Article  Google Scholar 

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Correspondence to Antonis Bikakis .

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Bikakis, A., Caire, P. (2015). Computing Coalitions in Multiagent Systems: A Contextual Reasoning Approach. In: Bulling, N. (eds) Multi-Agent Systems. EUMAS 2014. Lecture Notes in Computer Science(), vol 8953. Springer, Cham. https://doi.org/10.1007/978-3-319-17130-2_6

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  • DOI: https://doi.org/10.1007/978-3-319-17130-2_6

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