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A Non-cooperative Game-Theoretic Approach for Conflict Resolution in Multi-agent Planning

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A Non-cooperative Game-Theoretic Approach for Conflict Resolution in Multi-agent Planning

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Jordán, J.; Torreño Lerma, A.; De Weerdt, M.; Onaindia De La Rivaherrera, E. (2021). A Non-cooperative Game-Theoretic Approach for Conflict Resolution in Multi-agent Planning. Group Decision and Negotiation. 30(1):7-41. https://doi.org/10.1007/s10726-020-09703-0

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Título: A Non-cooperative Game-Theoretic Approach for Conflict Resolution in Multi-agent Planning
Autor: Jordán, Jaume Torreño Lerma, Alejandro de Weerdt, Mathijs Onaindia De La Rivaherrera, Eva
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
[EN] This paper presents FENOCOP, a game-theoretic approach for solving non-cooperative planning problems that involve a set of self-interested agents. Each agent wants to execute its own plan in a shared environment but ...[+]
Palabras clave: Planning , Multi-agent planning , Game theory , Nash equilibrium , Pareto optimal , Fairness
Derechos de uso: Reserva de todos los derechos
Fuente:
Group Decision and Negotiation. (issn: 0926-2644 )
DOI: 10.1007/s10726-020-09703-0
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/s10726-020-09703-0
Código del Proyecto:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-88476-C2-1-R/ES/RECONOCIMIENTO DE ACTIVIDADES Y PLANIFICACION AUTOMATICA PARA EL DISEÑO DE ASISTENTES INTELIGENTES/
info:eu-repo/grantAgreement/UPV//PAID-06-18/
info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//APOSTD%2F2018%2F010//CONTRATACION DE INVESTIGADOR POSTDOCTORAL GVA-JORDAN PRUNERA. PROYECTO: TECNOLOGIAS INTELIGENTES PARA OPTIMIZACION DE FLOTAS URBANAS DE VEHICULOS ELECTRICOS. /
info:eu-repo/grantAgreement/UPV-VIN//SP20180184//Técnicas inteligentes para optimización de la localización de estaciones de recarga de vehículos eléctricos y mejora de la movilidad en ciudades/
Agradecimientos:
This work is supported by the Spanish MINECO project TIN2017-88476-C2-1-R. Jaume Jordan is funded by grant APOSTD/2018/010 of Generalitat Valenciana - Fondo Social Europeo and by UPV PAID-06-18 project.
Tipo: Artículo

References

Blum A, Furst ML (1997) Fast planning through planning graph analysis. Artif Intell 90(1–2):281–300

Bowling MH, Jensen RM, Veloso MM (2003) A formalization of equilibria for multiagent planning. In: Proceedings of the 18th international joint conference on artificial intelligence (IJCAI), pp 1460–1462

Brafman RI, Domshlak C, Engel Y, Tennenholtz M. Planning games. In: Proceedings of the 21st international joint conference on artificial intelligence (IJCAI), pp 73–78 (2009) [+]
Blum A, Furst ML (1997) Fast planning through planning graph analysis. Artif Intell 90(1–2):281–300

Bowling MH, Jensen RM, Veloso MM (2003) A formalization of equilibria for multiagent planning. In: Proceedings of the 18th international joint conference on artificial intelligence (IJCAI), pp 1460–1462

Brafman RI, Domshlak C, Engel Y, Tennenholtz M. Planning games. In: Proceedings of the 21st international joint conference on artificial intelligence (IJCAI), pp 73–78 (2009)

Brandt F, Conitzer V, Endriss U, Lang J, Procaccia AD (eds) (2016) Handbook of computational social choice. Cambridge University Press, Cambridge

Buzing P, Mors AT, Valk J, Witteveen C (2006) Coordinating self-interested planning agents. Auton Agents Multi-Agent Syst 12(2):199–218. https://doi.org/10.1007/s10458-005-6104-4

Chevaleyre Y, Dunne PE, Endriss U, Lang J, LemaÎtre M, Maudet N, Padget J, Phelps S, Rodríguez-Aguilar JA, Sousa P (2006) Issues in multiagent resource allocation. Informatica 30(1):3–31

Crosby M, Rovatsos M (2011) Heuristic multiagent planning with self-interested agents. In: Proceedings of the 10th international conference on autonomous agents and multiagent systems (AAMAS), vol 1–3, pp 1213–1214

Endriss U, Maudet N, Sadri F, Toni F (2006) Others: negotiating socially optimal allocations of resources. J Artif Intell Res 25:315–348

Fikes R, Nilsson N (1971) STRIPS: A new approach to the application of theorem proving to problem solving. Artif Intell 2(3):189–208

Gal K, Procaccia AD, Mash M, Zick Y (2018) Which is the fairest (rent division) of them all? Commun ACM 61(2):93–100

Gerevini A, Serina I (2002) Lpg: a planner based on local search for planning graphs with action costs. In: Proceedings of the 6th international conference on artificial intelligence planning systems. AAAI Press, pp 13–22. http://dl.acm.org/citation.cfm?Id=3036884.3036887

Ghallab M, Nau D, Traverso P (2004) Automated planning: theory & practice. Elsevier, Amsterdam

Gillies DB (1959) Solutions to general non-zero-sum games. Contrib Theory Games 4(40):47–85

Jensen RM, Veloso MM, Bowling MH (2001) Obdd-based optimistic and strong cyclic adversarial planning. In: Proceedings of the 6th European conference on planning, pp 265–276

Jordán J, Onaindía E (2015) Game-theoretic approach for non-cooperative planning. In: Proceedings of the 29th AAAI conference on artificial intelligence (AAAI), pp 1357–1363

Komenda A, Stolba M, Kovacs DL (2016) The international competition of distributed and multiagent planners (CoDMAP). AI Mag 37(3):109–115

Larbi RB, Konieczny S, Marquis P (2007) Extending classical planning to the multi-agent case: a game-theoretic approach. In: Symbolic and quantitative approaches to reasoning With uncertainty, 9th European conference, ECSQARU, pp 731–742

McKelvey RD, McLennan AM, Turocy TL (2014) Gambit: software tools for game theory, version 13.1.2. http://www.gambit-project.org. Accessed 2 Oct 2015

Myerson RB (1981) Utilitarianism, egalitarianism, and the timing effect in social choice problems. Econometrica 49(4):883–897

Myerson RB (2013) Game theory. Harvard University Press, Cambridge

Nguyen N, Katarzyniak R (2009) Actions and social interactions in multi-agent systems. Knowl Inf Syst 18(2):133–136

Nissim R, Brafman R I (2013) Cost-optimal planning by self-interested agents. In: Proceedings of the 27th AAAI conference on artificial intelligence, pp 732–738. http://www.aaai.org/ocs/index.php/AAAI/AAAI13/paper/view/6384

Osborne MJ, Rubinstein A (1994) A course in game theory. MIT Press, Cambridge

Rawls J (1971) A theory of justice. Harvard University Press, Harvard Paperback

Sailer F, Buro M, Lanctot M (2007) Adversarial planning through strategy simulation. In: 2007 IEEE symposium on computational intelligence and games, pp 80–87. https://doi.org/10.1109/CIG.2007.368082

Shoham Y, Leyton-Brown K (2009) Multiagent systems: algorithmic, game-theoretic, and logical foundations. Cambridge University Press, Cambridge

Torreño A, Onaindia E, Komenda A, Stolba M (2018) Cooperative multi-agent planning: a survey. ACM Comput Surv 50(6):84:1–84:32

Torreño A, Onaindia E, Sapena Ó (2014) FMAP: distributed cooperative multi-agent planning. Appl Intell 41(2):606–626

Van Der Krogt R, De Weerdt M (2005) Self-interested planning agents using plan repair. In: ICAPS 2005 workshop on multiagent planning and scheduling, pp 36–44

Von Neumann J, Morgenstern O (2007) Theory of games and economic behavior. Princeton University Press, Princeton

Weerdt MD, Clement B (2009) Introduction to planning in multiagent systems. Multiagent Grid Syst 5(4):345–355

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