Against all noise
Authors
Department
Mathematisch-Naturwissenschaftliche Fakultät II
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Abstract
Für Kooperation via direkte Reziprozität müssen Menschen das Handeln ihrer Partner nachverfolgen, um Ausbeutung zu verhindern. Störungen (d.h. Gedächtnis- oder Wahrnehmungs-/Entscheidungsfehler) beeinträchtigen aber das Nachverfolgen. In meiner Dissertation erkunde ich, ob Strategien zur Modellierung menschlichen Verhaltens kognitiv umsetzbar sind und wie sie mit Störungen umgehen und erforsche umsetzbare störrobuste Alternativen. Tit-For-Tat, berühmtestes Beispiel traditioneller 1-Schritt-Gedächtnis-Strategien, ist nicht störrobust, weil kleinste Störungen seinen Erfolg verringern. Da Störungen alltäglich sind, ist Tit-For-Tat kein ideales Modell menschlichen Verhaltens. Kapitel 1 zeigte hohe Gedächtnisfehlerraten, wenn Versuchspersonen die letzte Handlung ihrer Partner wiedergeben sollten (1-Schritt-Gedächtnis). In einer evolutionären Simulation ging Kooperation bei diesen Raten unter. Sich an die letzte Handlung zu erinnern, ist weder störrobust noch umsetzbar. In Kapitel 2 untersuchte ich, ob Menschen die kognitiv eher umsetzbare Strategie benutzen, ihre Partner in Typen einzuteilen und Kooperierer/Betrüger zu unterscheiden. Verglichen damit, sich die letzte Handlung jedes Partners zu merken, sollte das die Gedächtnisanforderungen senken. Die Ergebnisse deuten an, daß Menschen Partnertypen unterscheiden und ihre Strategie an die Typenverteilung in der Umgebung anpassen. Kapitel 3 erforschte Strategien, die den Vorgang der Einteilung von Partnertypen modellieren, indem sie einen Eindruck bilden. In einer Simulation waren eindrucksbasierte Strategien beim Aufrechterhalten von Kooperation störrobuster als traditionelle Strategien. Auch sagten eindrucksbasierte Strategien Versuchspersonenverhalten besser vorher als traditionelle Strategien. Gewinner von Simulation und Kreuzvalidierung waren jedoch partnerunabhängige Strategien. Menschen scheinen kognitiv noch einfacher umsetzbare störrobuste Strategien zu benutzen.
For cooperation to evolve via direct reciprocity, individuals must track their partners’ behaviour to avoid exploitation. Noise (i.e., memory errors or perception/decision errors) compromises tracking, however. In my thesis, I investigate whether strategies proposed to model human behaviour are cognitively feasible and how they cope with noise, and explore feasible noise-robust alternatives. Tit-For-Tat, the most prominent example of 1-step memory strategies, is not robust to noise, because even little noise decreases its success. Since noise is quite common in everyday life, Tit-For-Tat is not an ideal candidate to model human behaviour. Chapter 1 showed that participants, when asked to remember their partners’ previous behaviour (1-step memory), had high memory error rates. In an evolutionary simulation, these rates let cooperation vanish. Remembering a partners’ previous behaviour is neither noise-robust nor cognitively feasible. In Chapter 2, I investigated whether people use the cognitively more feasible strategy of categorizing partners into types, distinguishing cooperators and cheaters. Compared to remembering each partners’ previous behaviour, this would reduce memory effort. The results indicate that people differentiate partner types and adjust their strategy to the proportion of types in their environment. Chapter 3 explored strategies that model the process of categorizing partners into types by building an impression. In a simulation, impression-based strategies were more robust to noise in maintaining cooperation than 1-step memory strategies. A cross-validation of strategies on data from Chapter 2 confirmed that impression-based strategies better predict participants’ behaviour than 1-step memory strategies. The winner of the simulation and the cross-validation were non-contingent strategies, though, indicating that people use cognitively even simpler noise-robust strategies.
For cooperation to evolve via direct reciprocity, individuals must track their partners’ behaviour to avoid exploitation. Noise (i.e., memory errors or perception/decision errors) compromises tracking, however. In my thesis, I investigate whether strategies proposed to model human behaviour are cognitively feasible and how they cope with noise, and explore feasible noise-robust alternatives. Tit-For-Tat, the most prominent example of 1-step memory strategies, is not robust to noise, because even little noise decreases its success. Since noise is quite common in everyday life, Tit-For-Tat is not an ideal candidate to model human behaviour. Chapter 1 showed that participants, when asked to remember their partners’ previous behaviour (1-step memory), had high memory error rates. In an evolutionary simulation, these rates let cooperation vanish. Remembering a partners’ previous behaviour is neither noise-robust nor cognitively feasible. In Chapter 2, I investigated whether people use the cognitively more feasible strategy of categorizing partners into types, distinguishing cooperators and cheaters. Compared to remembering each partners’ previous behaviour, this would reduce memory effort. The results indicate that people differentiate partner types and adjust their strategy to the proportion of types in their environment. Chapter 3 explored strategies that model the process of categorizing partners into types by building an impression. In a simulation, impression-based strategies were more robust to noise in maintaining cooperation than 1-step memory strategies. A cross-validation of strategies on data from Chapter 2 confirmed that impression-based strategies better predict participants’ behaviour than 1-step memory strategies. The winner of the simulation and the cross-validation were non-contingent strategies, though, indicating that people use cognitively even simpler noise-robust strategies.
Description
Keywords
Kooperation, Reziprozität, Störung, Strategien, reciprocity, strategies, noise, cooperation
Dewey Decimal Classification
150 Psychologie
Citation
Volstorf, Jenny.(2013). Against all noise. 10.18452/16709