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Abstract:

The minority game is a well-known agent-based model with no explicit interaction among its agents. However, it is known that they interact through the global magnitudes of the model and through their strategies. In this work we have attempted to formalize the implicit interactions among minority game agents as if they were links on a complex network. We have defined the link between two agents by quantifying the similarity between them. This link definition is based on the information of the instance of the game (the set of strategies assigned to each agent at the beginning) without any dynamic information on the game and brings about a static, unweighed and undirected network. We have analyzed the structure of the resulting network for different parameters, such as the number of agents (N) and the agent's capacity to process information (m), always taking into account games with two strategies per agent. In the region of crowd effects of the model, the resulting networks structure is a small-world network, whereas in the region where the behavior of the minority game is the same as in a game of random decisions, networks become a random network of Erdos-Renyi. The transition between these two types of networks is slow, without any peculiar feature of the network in the region of the coordination among agents. Finally, we have studied the resulting static networks for the full strategy minority game model, a maximal instance of the minority game in which all possible agents take part in the game. We have explicitly calculated the degree distribution of the full strategy minority game network and, on the basis of this analytical result, we have estimated the degree distribution of the minority game network, which is in accordance with computational results. © 2014 American Physical Society.

Registro:

Documento: Artículo
Título:Properties of interaction networks underlying the minority game
Autor:Caridi, I.
Filiación:Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Palabras clave:Computational methods; Telecommunication networks; Analytical results; Computational results; Degree distributions; Dynamic information; Implicit interaction; Interaction networks; Process information; Undirected network; Small-world networks
Año:2014
Volumen:90
Número:5
DOI: http://dx.doi.org/10.1103/PhysRevE.90.052816
Título revista:Physical Review E - Statistical, Nonlinear, and Soft Matter Physics
Título revista abreviado:Phys. Rev. E Stat. Nonlinear Soft Matter Phys.
ISSN:15393755
CODEN:PLEEE
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_15393755_v90_n5_p_Caridi

Referencias:

  • Von Neumann, J., Morgenstern, O., (1944) Theory of Games and Economic Behavior, , Princeton University Press, Princeton, NJ
  • Axelrod, R., (1984) The Evolution of Cooperation, , Basic Books, New York
  • Axelrod, R., (1997) The Complexity of Cooperation, , Princeton University Press, Princeton, NJ
  • Perc, M., Szolnoki, A., (2010) BioSystems, 99, p. 109. , BSYMBO 0303-2647
  • Szabó, G., Fath, G., (2007) Phys. Rep., 446, p. 97
  • Challet, D., Zhang, Y.C., (1997) Physica A, 246, p. 407. , PHYADX 0378-4371
  • Challet, D., Zhang, Y.C., (1998) Physica A, 256, p. 514. , PHYADX 0378-4371
  • Arthur, W.B., (1994) Am. Econ. Rev., 84, p. 406. , A.E.A. Papers and Proc
  • Cavagna, A., (1999) Phys. Rev. e, 59, p. R3783. , 1063-651X
  • Marsili, M., Challet, D., Zecchina, R., (2000) Physica A, 280, p. 522. , PHYADX 0378-4371
  • Challet, D., Marsili, M., (2000) Phys Rev. e, 62, p. 1862. , 1063-651X
  • Ho, K.H., Man, W.C., Chow, F.K., Chau, H.F., (2005) Phys. Rev. e, 71, p. 066120. , PLEEE8 1539-3755
  • Challet, D., Marsili, M., Zhang, Y.C., (2005) Minority Games, , Oxford University Press, Oxford
  • Challet, D., Marsili, M., Zecchina, R., (2000) Phys. Rev. Lett., 84, p. 1824. , PRLTAO 0031-9007
  • Acosta, G., Caridi, I., Guala, S., Marenco, J., (2012) Physica A, 391, p. 217. , PHYADX 0378-4371
  • Manuca, R., Li, Y., Savit, R., (2000) Physica A, 282, p. 559
  • Challet, D., Marsili, M., (1999) Phys. Rev. e, 60, p. R6271. , (R). 1063-651X
  • Caridi, I., Ceva, H., (2003) Physica A, 317, p. 247. , PHYADX 0378-4371
  • Ho, K.H., Chow, F.K., Chau, H.F., (2004) Phys. Rev. e, 70, p. 066110. , PLEEE8 1539-3755
  • Acosta, G., Caridi, I., Guala, S., Marenco, J., (2013) Physica A, 392, p. 4450
  • Cavagna, A., Garrahan, J.P., Giardina, I., Sherrington, D., (1999) Phys. Rev. Lett., 83, p. 4429. , PRLTAO 0031-9007
  • Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.H., (2006) Phys. Rep., 424, p. 175. , PRPLCM 0370-1573
  • Barabasi, A.L., Albert, R., (2002) Rev. Mod. Phys., 74, p. 47. , RMPHAT 0034-6861
  • Strogatz, S.H., (2001) Nature, 410, p. 268. , NATUAS 0028-0836
  • Moelbert, S., De Los Rios, P., (2002) Physica A, 303, p. 217. , PHYADX 0378-4371
  • Kalinowski, T., Schulz, H., Briese, M., (2000) Physica A, 277, p. 502. , PHYADX 0378-4371
  • Paczuski, M., Bassler, K.E., Corral, A., (2000) Phys. Rev. Lett., 84, p. 3185. , PRLTAO 0031-9007
  • Galstyan, A., Lerman, K., (2002) Phys. Rev. e, 66, p. 015103. , 1063-651X
  • Shang, L., Wang, X.F., (2007) Physica A, 377, p. 616. , PHYADX 0378-4371
  • Mello, B.A., Souza, V.M.C.S., Cajueiro, D.O., Andrade, R.F.S., (2010) Eur. Phys. J. B, 76, p. 147. , EPJBFY 1434-6028
  • Lo, T.S., Chan, H.Y., Hui, P.M., Johnson, N.F., (2004) Phys. Rev. e, 70, p. 056102. , PLEEE8 1539-3755
  • Caridi, I., Ceva, H., (2004) Physica A, 339, p. 574. , PHYADX 0378-4371
  • Hamming, R.W., (1950) Bell System Technical Journal, 29, p. 147
  • Frodesen, A.G., Skjeggestad, O., Tfte, H., (1979) Probability and Statistics in Particle Physics, , (Universitetsforl.)
  • Csardi, G., Nepusz, T., (2006) InterJournal Complex Systems, p. 1695
  • r Development Core Team, (2011) A Language and Environment for Statistical Computing, , r (R Foundation for Statistical Computing, Vienna, Austria)
  • Liaw, S.S., Liu, C., (2005) Physica A, 351, p. 571. , PHYADX 0378-4371
  • Stumpf, H.M.P., Wiuf, C., May, R.M., (2005) Proc. Natl. Acad. Sci. USA, 102, p. 4221. , PNASA6 0027-8424
  • Szolnoki, A., Perc, M., (2009) Europhys. Lett., 86, p. 30007. , EULEEJ 0295-5075

Citas:

---------- APA ----------
(2014) . Properties of interaction networks underlying the minority game. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 90(5).
http://dx.doi.org/10.1103/PhysRevE.90.052816
---------- CHICAGO ----------
Caridi, I. "Properties of interaction networks underlying the minority game" . Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 90, no. 5 (2014).
http://dx.doi.org/10.1103/PhysRevE.90.052816
---------- MLA ----------
Caridi, I. "Properties of interaction networks underlying the minority game" . Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, vol. 90, no. 5, 2014.
http://dx.doi.org/10.1103/PhysRevE.90.052816
---------- VANCOUVER ----------
Caridi, I. Properties of interaction networks underlying the minority game. Phys. Rev. E Stat. Nonlinear Soft Matter Phys. 2014;90(5).
http://dx.doi.org/10.1103/PhysRevE.90.052816