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

Yıl 2023, , 91 - 109, 10.08.2023

Burak Çetiner , Hakan Yaşarcan

https://doi.org/10.46465/endustrimuhendisligi.1264061

Öz

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.

Anahtar Kelimeler

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

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

Öz

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

Kaynakça

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