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Exploring the Generality of Norms in Multi-Agent Systems

  • Jhonatan Alves [1] ; Jomi Fred Hübner [1] ; Jerusa Marchi [1]
    1. [1] Federal University of Santa Catarina, Brasil
  • Localización: Inteligencia artificial: Revista Iberoamericana de Inteligencia Artificial, ISSN-e 1988-3064, ISSN 1137-3601, Vol. 26, Nº. 72, 2023, págs. 60-80
  • Idioma: inglés
  • DOI: 10.4114/intartif.vol26iss72pp60-80
  • Enlaces
  • Resumen
    • Norms are useful tools to regulate autonomous agents, and their generality is the focus of this paper. The generality of norms refers to the extent of behaviors the norms are capable of regulating. While very specific norms tend to be inefficient to avoid undesirable behaviors (since they are rarely activated), very general norms tend to limit excessively the options of the agents (since they are activated too often) hindering them to achieve the system goal. Therefore, a norm that efficiently regulates the agents should have a balanced generality, being neither too specific nor too general. Therefore, we consider that exploring the generality of norms is a fundamental key to obtaining efficient norms. However, the evaluation of their generality usually considers every behavior they regulate. Since it is likely an unfeasible task, in this paper, we investigate alternatives to estimate the norms generality from their syntactic characteristics. Based on these characteristics, we obtain different sequences of norms that vary, approximately, from the most specific to the most general. We assume thus that norms with a balanced generality are more easily found considering these orderings. Therefore, it is relevant to understand the impact of the syntactical characteristics in ordering the norms. In this context, we found out how different alternatives organize the norms space. This result is particularly useful for the development of algorithms for searching efficient norms that, through different strategies, may exploit how norms space is arranged and may be pruned.

  • Referencias bibliográficas
    • W. Alshabi, S. Ramaswamy, M. Itmi, and H. Abdulrab. Coordination, cooperation and conflict resolution in multi-agent systems. In Tarek Sobh,...
    • J. Alves, J. F. Hübner, and J. Marchi. The impact of norms generality on mas goal. In Proceedings of the 15th Workshop-School on Agents,...
    • K. G. Binmore. Natural Justice. Oxford scholarship online. Economics and finance module. Oxford University Press, 2005.
    • G. Boella and L. Lesmo. Deliberate normative agents. 05 2001.
    • G. Boella and L. van der Torre. Regulative and constitutive norms in normative multiagent systems. In Proceedings of the Ninth International...
    • G. Boella, L. van der Torre, and H. Verhagen. Introduction to normative multiagent systems. Computation and Mathematical Organizational Theory,...
    • M. Bramer. Logic Programming with Prolog. Springer Publishing Company, Incorporated, 2nd edition, 2014.
    • N. Bulling and M. Dastani. Verifying normative behaviour via normative mechanism design. pages 103–108, 01 2011.
    • H. L. Cardoso and E. Oliveira. Institutional reality and norms: Specifying and monitoring agent organizations. International Journal of Cooperative...
    • G. Christelis and M. Rovatsos. Automated norm synthesis in an agent-based planning environment. In Proceedings of The 8th International Conference...
    • R. Conte and C. Castelfranchi. Understanding the effects of norms in social groups through simulation. Artificial Societies: The Computer...
    • N. Criado, E. Argente, and V. Botti. Open issues for normative multi-agent systems. AI Commun., 24:233– 264, 01 2011.
    • F. J. P. da Cunha, T. F. M. Sirqueira, M. L. Viana, and C. J. P. de Lucena. Extending bdi multiagent systems with agent norms. International...
    • M. Dastani, J. Dix, H. Verhagen, and S. Villata. Normative Multi-Agent Systems (Dagstuhl Seminar 18171). Dagstuhl Reports, 8(4):72–103, 2018.
    • I. J. B. do Nascimento, N. Cacic, H. M. Abdulazeem, T. C. von Groote, U. Jayarajah, I. Weerasekara, M. A. Esfahani, V. T. Civile, A. Marusic,...
    • M.A. Eggert, M. Eggert, and W. Falzon. The Resolving Conflict Pocketbook. Management Pocketbooks Series. Management Pocketbooks, 2004.
    • L. Ekenberg. Detecting conflicts in multi-agent systems. In C. Zhang and D. Lukose, editors, Multi-Agent Systems: Methodologies and Applications....
    • D. Fitoussi and M. Tennenholtz. Minimal social laws. In Proceedings of the Fifteenth National/Tenth Conference on Artificial Intelligence/Innovative...
    • D. Fitoussi and M. Tennenholtz. Choosing social laws for multi-agent systems: Minimality and simplicity. Artificial Intelligence, 119(1):61–101,...
    • A. Garćıa-Camino, P. Noriega, and J. Rodŕıguez-Aguilar. Implementing norms in electronic institutions. pages 667–673, 01 2005.
    • K. V. Hindriks, F. S. De Boer, W. van der Hoek, and J. Meye. Agent programming with declarative goals. 01 2001.
    • N. Khan. Critical review of sampling techniques in the research process in the world. 2020.
    • J. Morales, M. López-Sánchez, J. Rodŕıguez-Aguilar, M. Wooldridge, and W. Vasconcelos. Minimality and simplicity in the on-line automated...
    • J. Morales, M. Lopez-Sanchez, J. A. Rodriguez-Aguilar, M. Wooldridge, and W. Vasconcelos. Automated synthesis of normative systems. In Proc....
    • I. Pratt. Closed World Assumptions, pages 65–84. Macmillan Education UK, London, 1994.
    • T. Ågotnes and M. Wooldridge. Optimal social laws. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent...
    • S. Resmerita and M. Heymann. Conflict resolution in multi-agent systems. volume 3, pages 2537 – 2542 Vol.3, 01 2004.
    • M. Riad and F. Golpayegani. Run-time norms synthesis in multi-objective multi-agent systems. CoRR, abs/2105.00124, 2021.
    • J. A. Robinson. Computational logic: The unification computation. Machine intelligence, 6:63–72, 1971.
    • S. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, 3 edition, 2010.
    • F. P. Santos. Social norms of cooperation in multiagent systems. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent...
    • Y. Shoham and M. Tennenholtz. On social laws for artificial agent societies: off-line design. Artificial Intelligence, 73(1):231–252, 1995.
    • C. Tessier, L. Chaudron, and H. Müller, editors. Conflicting Agents: Conflict Management in Multi-Agent Systems. Kluwer Academic Publishers,...
    • M. B. van Riemsdijk, M. Dastani, and M. Winikoff. Goals in agent systems: a unifying framework. pages 713–720, 01 2008.
    • T. Yang, J. Hao, Z. Meng, and Z. Wang. Norm Emergence in Multiagent Systems, chapter Chapter 8, pages 179–206. 2018.

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