Abramson G, Kuperman M (2001) Social games in a social network. Phys Rev E 63
Axelrod R (1984) The evolution of cooperation. Basic Books, New York
Google Scholar
Babes M, Cote EMD, Littman ML (2008) Social reward shaping in the prisoner’s dilemma. In: Padgham L, Parkes D, Müller J, Parsons S (eds) Proc. of the 7th int. joint conf. on aut. agents and multiagent systems, IFAAMAS, May 2008, pp 1389–1392
Google Scholar
Bazzan ALC, Bordini RH (2001) A framework for the simulation of agents with emotions: Report on experiments with the iterated prisoners dilemma. In: Müller JP, Andre E, Sen S, Frasson C (eds) Proceedings of the fifth international conference on autonomous agents, Montreal, Canada, May 2001. ACM, New York, pp 292–299
Chapter
Google Scholar
Bazzan ALC, Bordini RH, Campbell JA (1999) Moral sentiments in multi-agent systems. In: Intelligent agents V. Lecture notes in artificial intelligence, vol 1555. Springer, Berlin, pp 113–131. Also appeared as Proc. of the workshop on agent theories, architecture and languages (ATAL98), Paris, July 1998
Google Scholar
Bazzan ALC, de Oliveira D, da Silva BC (2010) Learning in groups of traffic signals. Eng Appl Artif Intell 23:560–568
Article
Google Scholar
Brafman RI, Tennenholtz M (2002) Efficient learning equilibrium. In: NIPS, pp 1603–1610
Google Scholar
Claus C, Boutilier C (1998) The dynamics of reinforcement learning in cooperative multiagent systems. In: Proceedings of the fifteenth national conference on artificial intelligence, pp 746–752
Google Scholar
Costa-Montenegro E, Burguillo-Rial JC, González-Castaño FJ, Vales-Alonso J (2007) Agent-controlled sharing of distributed resources in user networks. In: Lee RST, Loia V (eds) Computational intelligence for agent-based systems. Studies in computational intelligence, vol 72. Springer, Berlin, pp 29–60
Chapter
Google Scholar
Costa-Montenegro E, Burguillo-Rial JC, Gil-Castiñeira F, González-Castaño FJ (2011) Implementation and analysis of the bittorrent protocol with a multi-agent model. J Netw Comput Appl 34:368–383
Article
Google Scholar
Fulda N, Ventura D (2007) Predicting and preventing coordination problems in cooperative Q-learning systems. In: Proceedings of the 20th international joint conference on artificial intelligence (IJCAI), pp 780–785
Google Scholar
Hines G, Larson K (2008) Learning when to take advice: A statistical test for achieving a correlated equilibrium. In: McAllester DA, Myllymäki P (eds) UAI. AUAI Press, Menlo Park, pp 274–281
Google Scholar
Hu J, Wellman MP (1998) Multiagent reinforcement learning: Theoretical framework and an algorithm. In: Proc. 15th international conf. on machine learning. Kaufmann, Los Altos, pp 242–250
Google Scholar
Huberman BA, Glance NS (1993) Evolutionary games and computer simulations. Proc Natl Acad Sci USA 90:7716–7718
Article
Google Scholar
Humphrys M (1997) Action selection methods using reinforcement learning. PhD thesis, Cambridge
Kim BJ, Trusina A, Holme P, Minnhagen P, Chung JS, Choi MY (2002) Dynamic instabilities induced by asymmetric influence: Prisoner’s dilemma game in small-world networks. Phys Rev E 66
Kuminov D, Tennenholtz M (2008) As safe as it gets: Near-optimal learning in multi-stage games with imperfect monitoring. In: Proceeding of the ECAI. IOS Press, Amsterdam, pp 438–442
Google Scholar
Lin R, Kraus S, Shavitt Y (2007) On the benefits of cheating by self-interested agents in vehicular networks. In: Proceedings of the 6th international joint conference on autonomous agents and multiagent systems (AAMAS 2007). ACM, New York, pp 327–334
Google Scholar
Lindgren K, Nordahl M (1994) Evolutionary dynamics of spatial games. Physica D 75:292–309
Article
Google Scholar
Littman ML (1994) Markov games as a framework for multi-agent reinforcement learning. In: Proceedings of the 11th international conference on machine learning, ML, New Brunswick, NJ. Kaufmann, Los Altos, pp 157–163
Google Scholar
Littman ML (2001) Friend-or-Foe Q-learning in general-sum games. In: Proceedings of the eighteenth international conference on machine learning (ICML01), San Francisco, CA, USA. Kaufmann, Los Altos, pp 322–328
Google Scholar
Mailath G, Samuelson L, Shaked A (1993) Correlated equilibria as network equilibria. Discussion paper, University of Bonn
Narendra KS, Thathachar MAL (1989) Learning automata: an introduction. Prentice-Hall, Upper Saddle River
Google Scholar
Nowak MA, May RM (1992) Evolutionary games and spatial chaos. Nature 359:826–829
Article
Google Scholar
Ortony A, Clore GL, Collins A (1988) The cognitive structure of emotions. Cambridge University Press, Cambridge
Book
Google Scholar
Panait L, Luke S (2005) Cooperative multi-agent learning: The state of the art. Auton Agents Multi-Agent Syst 11(3):387–434
Article
Google Scholar
Peleteiro A, Burguillo JC, Bazzan ALC (2010) Enhancing cooperation in the ipd with learning and coalitions. In: Proc. of the 2nd Brazilian workshop on social simulation, S. Bernardo do Campo. SBC, Porto Alegre
Google Scholar
Sandholm T (2007) Perspectives on multiagent learning. Artif Intell 171(7):382–391
Article
MathSciNet
Google Scholar
Sandholm TW, Crites RH (1995) Multiagent reinforcement learning in the iterated prisoner’s dilemma. Biosystems 37:147–166
Article
Google Scholar
Sandholm T, Larson K, Andersson M, Shehory O, Tohmé F (1999) Coalition structure generation with worst case guarantees. Artif Intell 111(1–2):209–238
Article
Google Scholar
Shoham Y, Powers R, Grenager T (2007) If multi-agent learning is the answer, what is the question? Artif Intell 171(7):365–377
Article
MathSciNet
Google Scholar
Stone P (2007) Multiagent learning is not the answer. It is the question. Artif Intell 171(7):402–405
Article
Google Scholar
Stone P, Veloso M (2000) Multiagent systems: A survey from a machine learning perspective. Auton Robots 8(3):345–383
Article
Google Scholar
Vinyals M, Rodríguez-Aguilar JA, Cerquides J (2011) A survey on sensor networks from a multiagent perspective. Comput J 54:455–470
Article
Google Scholar
Vrancx P, Tuyls K, Westra RL (2008) Switching dynamics of multi-agent learning. In: Padgham L, Parkes D, Müller J, Parsons S (eds) Proceedings of the 7th international joint conference on autonomous agents and multiagent systems, Estoril, vol 1. pp 307–313
Google Scholar
Wang X, Sandholm T (2002) Reinforcement learning to play an optimal Nash equilibrium in team Markov games. In: Advances in neural information processing systems (NIPS-2002), vol 15
Google Scholar
Watkins CJCH, Dayan P (1992) Q-learning. Mach Learn 8(3):279–292
Google Scholar
Zhang C, Abdallah S, Lesser VR (2008) Efficient multi-agent reinforcement learning through automated supervision (extended abstract). In: Padgham L, Parkes D, Müller J, Parsons S (eds) Proceedings of the 7th international joint conference on autonomous agents and multiagent systems, Estoril, vol 3. pp 1365–1368
Google Scholar
Zhang C, Abdallah S, Lesser V (2009) Integrating organizational control into multi-agent learning. In: Sichman JS, Decker KS, Sierra C, Castelfranchi C (eds) Proceedings of the 8th international conference on autonomous agents and multiagent systems (AAMAS), Budapest, Hungary
Google Scholar