The El Farol Bar Problem: Karar Vermede Kullanılan Farklı Beklenti Modellerinin Karşılaştırılmalı Analizi

Arthur (1994) “Bounded Rationality and Inductive Reasoning” adlı makalesinde El Farol Bar Problemini (EFBP) tanıtmaktadır. EFBP'nin etmen tabanlı bir modelini oluşturmakta ve bunu "sınırlı rasyonellik" kavramının önemini açıklamak için kullanmaktadır. Arthur'a göre, tümdengelimli akıl yürütme, EFBP için istenen bir davranışı üretecek kararlar oluşturamayacaktır. Bu nedenle, karar vermede tümevarımsal akıl yürütmeyi kullanan sınırlı rasyonel ajanlar, bu ve benzeri türdeki problemler için bir zorunluluktur. Bu çalışmada, Arthur'un çalışmasını farklı beklenti modelleri kullanan ajanlar oluşturarak genişletiyoruz ve onları ortalama katılım ve standart sapma gibi performans ölçütleri açısından karşılaştırıyoruz. Ajanların genel performansında bir gelişme bekleyerek katılım kararlarını oluştururken tümevarımsal muhakemeyi kullanan adaptif öğrenme yöntemini kullanıyoruz. EFBP analizi boyunca, haftalık katılım bilgisini kullanmanın olumsuz etkisini ve heterojenliğin rolünü keşfediyoruz. Bulgularımıza göre, beklemediğimiz şekilde adaptif öğrenen ajanların davranışı, tümdengelimli muhakeme kullanan ajanlardan beklenebilecek davranışa yakınsıyor.

Anahtar Kelimeler:

ajan temelli benzetim, el farol bar problemi, karar verme

The El Farol Bar Problem: A Comparative Analysis of Expectation Models Used in Decision Making

Arthur (1994) introduces the El Farol Bar Problem (EFBP) in his article “Bounded Rationality and Inductive Reasoning". He creates an agent-based model of the EFBP and uses it to explain the importance of the concept "bounded rationality". According to Arthur, deductive reasoning will not create decisions that will produce a desired behavior for the EFBP. Hence, boundedly rational agents using inductive reasoning in decision making is a must for this and similar type of problems. We extend Arthur's work by creating different types of agents and compare them in terms of performance measures such as mean attendance and standard deviation of attendance. We introduce adaptive learning agents that use inductive reasoning in forming their decisions expecting an improvement in the overall performance of the agents. Throughout the analysis of the EFBP, we discover the role of the heterogeneity and the detrimental effect of using the weekly attendance information. Unexpectedly, as a result of our findings, the behavior of adaptive learning agents converges to the behavior that would be expected from agents using deductive reasoning.

Keywords:

agent based simulation, El Farol Bar Problem, decision-making,

PDF

___

Adler, J. L. & Blue, V. J. (2002), A cooperative multi-agent transportation management and route guidance system, Transportation Research Part C: Emerging Technologies,. 10 (5-6), 433-454. Doi : https://doi.org/10.1016/S0968-090X(02)00030-X
Arthur, W. B. (1994), Inductive reasoning and bounded rationality, The American Economic Review, 84(2), 406-411. Retrieved from https://www.jstor.org/stable/2117868
Arthur, W. B. (1999), Complexity and the economy, Science, 284(5411), 107-109. Doi: https://doi.org/10.1126/science.284.5411.10
Chakrabarti, B. K. (2007), Kolkata restaurant problem as a generalised El Farol bar problem, Econophysics of Markets and Business Networks, 239-246. Doi: https://doi.org/10.1007/978-88-470-0665-2_18
Challet, D., & Zhang, Y. C. (1997), Emergence of cooperation and organization in an evolutionary game, Physica A: Statistical Mechanics and its Applications, 246(3-4), 407-418. Doi: https://doi.org/10.1016/S0378-4371(97)00419-6
Chen, S. H. & Gostoli, U. (2017), Coordination in the el farol bar problem: the role of social preferences and social networks, Journal of Economic Interaction and Coordination, 12(1), 59-93. Doi: https://doi.org/10.1007/s11403-015-0150-z
De Cara, M. A. R., Pla, O. & Guinea, F. (1999), Competition, efficiency and collective behavior in the “El Farol” bar model, The European Physical Journal B-Condensed Matter and Complex Systems, 10(1), 187-191. Doi: https://doi.org/10.1007/s100510050843
Edmonds, B. (1998), Gossip, sexual recombination and the El Farol Bar: Modelling the emergence of heterogeneity, IFAC Proceedings Volumes, Cambridge, 31(16), 219-225. Doi: https://doi.org/10.1016/S1474-6670(17)40485-X
Elsner, W. (2017), Complexity economics as heterodoxy: Theory and policy, Journal of Economic Issues, 51(4), 939-978. Doi: https://doi.org/10.1080/00213624.2017.1391570
Fogel, D. B., Chellapilla, K. & Angeline, P. J. (1999). Inductive reasoning and bounded rationality reconsidered, Transactions on Evolutionary Computation, 3(2), 142-146. Doi: https://doi.org/10.1109/4235.771167
Foxon, T. J., J. Köhler, Michie, J. & Oughton, C. (2013), Towards a new complexity economics for sustainability, Cambridge Journal of Economics, 37(21), 187-208. Doi: https://doi.org/10.1093/cje/bes057
Galib, S. M. & Moser, I. (2011), Road trafic optimisation using an evolutionary game, in Proceedings of the 13th Annual Conference Companion on Genetic and Evolutionary Computation, Dublin, 519-526. Doi: https://doi.org/10.1145/2001858.2002043
Galstyan, A., Kolar, S. & Lerman, K. (2003), Resource allocation games with changing resource capacities, in Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, New York, 145-152. Doi: https://doi.org/10.1145/860575.860599
Gardner Jr, E. S. (1985). Exponential smoothing: The state of the art. Journal of Forecasting, 4(1), 1-28. Doi: https://doi.org/10.1002/for.3980040103
Garofalo, M. (2006), Modeling the El Farol Bar Problem in NetLogo, Preliminary Draft, Dexia Bank Belgium. Retrieved from http://ccl.northwestern.edu/2006/ElFarol.pdf
Hausken, K., S. Banuri, Gupta, D. K. & Abbink, K. (2015), Al Qaeda at the Bar: Coordinating ıdeologues and mercenaries in terrorist organizations, Public Choice, 164(1), 57-73. Doi: https://doi.org/10.1007/s11127-015-0261-z
Lustosa, B. C. & Cajueiro, D. O. (2010), Constrained ınformation minority game: how was the night at El Farol?, Physica A: Statistical Mechanics and its Applications, 389(6), 1230-1238. Doi: https://doi.org/10.1016/ j.physa.2009.11.034
Manson, S. M. (2001), Simplifying complexity: A review of complexity theory, Geoforum, 32(3), 405-414. Doi: https://doi.org/10.1016/S0016-7185(00)00035-X
Ponsiglione, C., Roma, V., Zampella, F. & Zollo, G. (2015). The fairness/efficiency issue explored through El Farol bar model, Scientific Methods for the Treatment of Uncertainty in Social Sciences, 309-327. Doi: https://doi.org/10.1007/978-3-319-19704-3_26
Rand, W. & Stonedahl, F. (2007). The El Farol bar problem and computational effort: Why people fail to use bars efficiently, Northwestern University, Evanston, IL. Retrieved from https://ccl.northwestern.edu/papers/2007/ Rand&Stonedahl_ElFarolBar.pdf
Sellers, M. W., Sayama, H. & Pape, A. D. (2020), Simulating systems thinking under bounded rationality, Complexity, 2020, 1-12. Doi: https://doi.org/10.1155/ 2020/3469263
Simon, H. A. (1980). Utility and Probability: Bounded Rationality, London, UK: Palgrave Macmillan.
Sterman, J. D. (1987). Systems simulation. expectation formation in behavioral simulation models, Behavioral Science, 32(3), 190-211. Doi: https://doi.org/10.1002/bs.3830320304
St Luce, S. & Sayama, H. (2020), Phase Spaces of the strategy evolution in the El Farol bar problem, The Conference on Artificial Life, 558-566. Doi: https://doi.org/10.1162/isal_a_00339
Wilensky, U. & Rand, W. (2015), An Introduction to Agent-based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo, Cambridge, UK: MIT Press.

ISSN: 1300-3410
Yayın Aralığı: Yılda 3 Sayı
Başlangıç: 1989
Yayıncı: TMMOB MAKİNA MÜHENDİSLERİ ODASI

Arşiv