Inductive reasoning and bounded rationality reconsidered

Fogel, David B.; Chellapilla, Kumar; Angeline, Peter J.

doi:10.1109/4235.771167

Cited by 49 publications

(33 citation statements)

References 5 publications

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“…Some systems, on the other hand, seem to allow analysis as if agents were rational [11], even though this may not be the case. Such systems are of particular interest, since they allow the use of traditional, tractable techniques for behavioral analysis [6].…”

Section: Introductionmentioning

confidence: 99%

Neural-Evolutionary Learning in a Bounded Rationality Scenario

Araújo

Lamb

2004

Neural Information Processing

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Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of a population of neural networks in order to make a decision, while inductive learning is performed by means of an evolutionary algorithm. We show that good convergence to the game-theoretic equilibrium is reached within certain parameters.

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Section: Introductionmentioning

confidence: 99%

Neural-Evolutionary Learning in a Bounded Rationality Scenario

Araújo

Lamb

2004

Neural Information Processing

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“…Simulations show that, as in the original model, the attendance at the bar fluctuates around the threshold level, and does not seem to settle down into any regular pattern. Another work where the agents' strategies are allowed to co-evolve is that of Fogel et al (1999). In the model they conomics Discussion Paper propose, the agents are endowed with 10 predictors that take the form of autoregressive models with the number of lag terms and the relative coefficients being the variables that evolve over time using evolutionary programming.…”

Section: Learning In the El Farol Bar Problemmentioning

confidence: 99%

“…Briefly put, there are two kinds of learning mechanism being studied in the literature. The first one is best-response learning (Arthur, 1994;Edmonds, 1999;Fogel et al, 1999;Challet et al, 2004;Atilgan, Atilgan and Demirel, 2008) and the second one is reinforcement learning (Bell and Sethares, 1999;Franke, 2003;Zambrano, 2004;Whitehead, 2008). 1 The typical results are as follows.…”

Section: El Farol Bar Problem: From Efficiency To Equitymentioning

confidence: 99%

Coordination in the El Farol Bar problem: The role of social preferences and social networks

Chen

Gostoli

2012

2012 IEEE Congress on Evolutionary Computation

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Shu-Heng Chen and Umberto GostoliAbstract In this paper, the authors continue the pursuit of the self-coordination mechanism as studied in the El Farol Bar problem. However, in addition to efficiency (the optimal use of the public facility), they are also interested in the distribution of the public resources among all agents. Hence, they introduce a two-dimensional El Farol Bar problem, to be distinguished from the early one-dimensional one, which has efficiency as the only concern. The authors ask whether it is possible to have selfcoordinating solutions to the El Farol Bar problem so that the public resources can be optimally used with neither idle capacity nor incurring congestion and, in the meantime, the resources can be well distributed among all agents. They consider this ideal situation an El Farol version of a "good society". This paper shows the existence of a positive answer to this inquiry, but it requires two elements, which were largely left out in the conventional literature on the El Farol Bar problem. These elements are social networks and social preferences. The authors first show, through cellular automata, that social networks can contribute to the emergence of a "good society". They then show that the addition of some inequity-averse agents can even guarantee the emergence of the "good society". JEL B52 C63 C73

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“…These situations can be modeled as coordination games; in which agents are expected to select the majority strategiy 13,14 . However, traditional game theory, does not consider how agents know which equilibrium should be realized if a coordination game has multiple and equally plausible Pareto-ranked equilibria 15,16 . This limitation is all the more surprising in games with common goal because one expects that players will coordinate to the Paretodominant equilibrium 17 .…”

Section: Modelmentioning

confidence: 99%

Influence of Partner Selection on Functional Differentiation: Emergence of Diversity by Isolated Interaction and Preference Change

Iwanaga

Namatame

2017

JRNAL

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When examining collective behavior, we focus on the interactions of individuals. We must also consider the microscopic level, where individual agent decisions occur, and the macroscopic level, where collective behavior can be observed. Collective behavior is both interesting and difficult because aggregate outcomes must be evaluated within environmental constraints. The performance of a collective system strongly depends on the type of interaction and heterogeneity of agent preference.In this study, relative to the emergence of diversity, we found that two different learning processes are required. In addition, we found that isolated interactions are required for the emergence of diversity. However, the utility of less clustered interactions is greater than that of isolated interactions. We found that isolated interactions are effective for the emergence of diversity. Once diversity emerges sufficiently, less clustered interactions are effective relative to the utility of each agent and the entire population.

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Inductive reasoning and bounded rationality reconsidered

Cited by 49 publications

References 5 publications

Neural-Evolutionary Learning in a Bounded Rationality Scenario

Neural-Evolutionary Learning in a Bounded Rationality Scenario

Coordination in the El Farol Bar problem: The role of social preferences and social networks

Influence of Partner Selection on Functional Differentiation: Emergence of Diversity by Isolated Interaction and Preference Change

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