Experimental implementations of the Ultimatum Game are some of the most well studied economic experiments of the last twenty years. There are two popular explanations for why Proposers offer substantially more than the smallest positive amount of the pie. One is that the Proposers have other-regarding preferences and the other explanation is that Proposers are selfish, but fear rejection by Responders who will reject low offers. Most experiments that attempt to discriminate between these two explanations contrast behavior in the Ultimatum Game to behavior in the Dictator Game. The Dictator Game removes strategic concerns from the Ultimatum Game without substantially changing the predicted behavior of a selfish Proposer. Researchers thus believe that subtracting Dictator Game offers from Ultimatum Game offers isolates the fraction of average offers in the Ultimatum Game motivated by other-regarding preferences. In most Dictator Game experiments, Proposers offer less than they do in Ultimatum Games, but they still offer non-trivial positive amounts. This result has led analysts to posit that Proposer behavior in the Ultimatum Game is motivated in part by other-regarding preferences. There are, however, potential problems in drawing inferences about Proposer behavior in the Ultimatum Game from observations of Proposer behavior in the Dictator Game. First, it is well known that objectively irrelevant contextual details in experiments can affect subject behavior in systematic ways. Second, altruistic motivations are less costly to satisfy per monetary unit in the Ultimatum Game because each monetary unit offered to the Responder reduces the probability of rejection. Thus strategic motivations may be sufficient to explain behavior in the Ultimatum Game. In other words, a Proposer with altruistic preferences may offer the same amount of money as an identical Proposer who differs only in his lack of such preferences. In contrast to previous approaches that remove the strategic incentives in the Ultimatum Game, we remove the incentives for expressing other-regarding preferences. We do so through a treatment in which humans are paired with robots that, for each choice in the Proposer’s decision space, reject with the same frequency as humans in previous experiments. Proposers are aware they are playing with automata that are programmed to reject and accept as humans have done in previous implementations of the experiment. Under the mild assumption that humans do not express other-regarding preferences for fictional automata, this treatment presents an Ultimatum Game with only strategic motives operative. Note also that unlike previous attempts that use a different game to make inferences about behavior in the Ultimatum Game, we are able to measure the effects of strategic and other-regarding motives without changing the fundamental structure of the Ultimatum Game. Moreover, previous analyses do not formally include decision error as an important motivation for non-SPNE offers. To test for misunderstanding of the strategic environment, we develop a second treatment in which subjects play the Ultimatum Game with a robot Responder that rejects or accepts every offer with equal probability. If Proposers are truly thinking about Responder rejection rates in formulating their offers, they should offer $0 in this treatment.

Theories that formally describe decision-making have traditionally posited that decisions are made by rational actors. However, it is generally accepted that humans often make irrational decisions because of quick emotional judgements. In order to reconcile these two inconsistent ideas psychologists have developed two-system theories that hypothesize decisions are made by two opposing cognitive systems, representing the rational and emotional processing of decisions. Evidence for a two-system model of decision-making can be observed in ultimatum game responder decisions. It is thought that rational processing of these choices will produce acceptance of unfair offers and emotional processing will encourage rejection of unfair offers. Emotional priming has been shown to decrease ultimatum game acceptances and trans-cranial magnetic stimulation of rational brain areas, i.e. DLPFC, show increases in ultimatum game acceptances. This study investigated the possibility of using behavioral tasks that are known to activate rational brain areas to promote/disrupt ultimatum game acceptances. The possible relationship between ultimatum game acceptances and executive functions was also examined. Although there were promising indications that working memory loading may increase ultimatum game acceptances in between-subject experiments, a within-subject investigation found little support for this method of promoting/disrupting rational ultimatum game decisions. There were also no relationships found between switching or inhibition executive functions and ultimatum game responder decisions. A moderate positive relationship was found between updating executive function and ultimatum game acceptance rates but this relationship was dependent on working memory task feedback, a within-subject design and active loading of the working memory system. However, its possible that these findings only apply to within-subject paradigms and future between-subject studies are advised.

Punishment is the act of penalizing an individual as a response to a transgression. This thesis will deal with punishment in experimental game scenarios and in experimental criminal punishment scenarios, along with their different adaptations. The aim will be to provide an overview of both psychological and neurological underpinnings of punishment by reviewing existing literature. While punishment ought to deter transgressions and promote cooperative behavior, internal neural reward-related systems seem to be a driving factor of the desire to punish wrongdoings. Decisions on whether a transgressor is guilty and deserves punishment is mediated by the medial prefrontal cortex with an emphasis on the ventromedial parts. External influences affect the behavioral output and its underlying neural signatures of punishment. Social context such as peer pressure and in-group bias emphasize the importance of theory of mind related areas when conducting punishment.

Fairness is an important topic that has captured the interest of researchers in many fields. Looking at behavioural and experimental economics, various methods have been used to shed the light on fairness. One of the most recognizable ways is through the use of the ultimatum game. In this paper, we aimed to look at fairness considerations by utilizing this game, while also highlighting gender and culture as factors of importance. Two models, specifically Rabin’s reciprocity model and Fehr and Schmidt’s inequity aversion model, in addition to various research papers on the topics of gender and culture, were used as the cornerstones for this paper. The experimental design was a replication of the ultimatum game, which was carried out online. Results showed that there were noticeable effects from both gender and culture on the behaviour of the participants in the game. However, the results were not statistically significant enough to be considered as determining factors in regard to why individuals behave in a specific manner in the game. Since research from the field has reached mixed conclusions, we can say that making inferences about human behaviour is harder than one might think.

No description available.

La vengeance réfère à la tentative de blesser ou de faire du mal à celui qui nous a causé du tort par sa faute. Alors que la vengeance se rapporte à l’action, le désir de vengeance réfère à l’émotion qui motive à la vengeance. La colère est une émotion ressentie lorsque nous subissons un dommage (interférence subite à la poursuite d’un but que nous tenons à coeur), alors que la rancune est une émotion qui est suscitée par la perception d’avoir ou le fait d’avoir réellement souffert d’une faute (préjudice qui est infligé de manière responsable d’un individu à une victime). Ces définitions de la colère et de la rancune peuvent se traduire de manière opérationnelle par le fait de provoquer des participants de façon qu’ils perçoivent cela comme accidentelle (sans faute) ou personnelle (avec faute) ; la première provocation induirait un état émotionnel de colère alors que la seconde de rancune. Les études passées ont démontré l’effet de la colère sur le taux de rejets d’offres monétaires très injustes et moyennement injustes comparativement aux offres justes lors d’une tâche de prise de décision économique tel que la tâche Ultimatum Game (UG) ainsi que sur l’amplitude de la Feedback-Related Negativity (FRN), une composante de potentiel reliés aux évènements qui devient plus prononcée lors d’une rétroaction négative associée à des résultats défavorable (ex., réponses incorrectes ou pertes monétaires). Ces données suggèrent que la colère augmenterait l’évaluation affective négative associée aux offres très injustes et moyennement injustes et les comportements de vengeance associés aux taux de rejet. Le rôle des émotions dans la vengeance pose la question de savoir si leur influence se transmet directement dans les comportements de vengeance. Le trait de vengeance réfère à la tendance dispositionnelle à entretenir des attitudes positives envers la vengeance et à la rechercher en réponse à des provocations. Les études antérieures ont démontré que le trait d’affects négatifs modérait la relation entre l'état affects négatifs et l’ampleur de la FRN. Il y a un manque dans nos connaissances sur le rôle du trait de vengeance sur la relation entre l’amplitude de la FRN et le taux de rejet d’offres monétaires. Le premier objectif de la présente étude est de comparer les effets de la colère à ceux de la rancune sur le taux de rejets d’offres monétaires justes, moyennement injustes et très injustes ainsi que sur la FRN durant la tâche UG. Le second objectif est de vérifier le rôle de modérateur du trait de vengeance sur la relation entre la FRN et le taux de rejet des offres, et ce en réponse à des offres très injustes et moyennement injustes. Deux groupes expérimentaux ont été créés : le groupe Colère (GrC) et le groupe Rancune (GrR). Le premier groupe a subi une induction de colère par le biais d'une provocation humaine sans faute pendant la réalisation d'une tâche de créativité. Au cours de la même tâche de créativité, les participants du second groupe ont été soumis à une induction de rancune par le biais d'une provocation humaine avec faute. Ensuite, il a été demandé aux participants de participer à la tâche UG, dans lequel ils devaient accepter ou rejeter des offres monétaires très injustes, moyennement injustes et justes proposées par un participant fictif. En plus de l’analyse du taux de rejet, le signal électroencéphalographique (EEG) a été quantifié puis analysé sur la FRN dans le but de servir de proxy de la perception d’injustice et du niveau de complexité de la prise de décision en fonction du groupe de participants et du type d’offres. Contrairement à ce qui était attendu, les résultats indiquent que le taux de rejet des participants du GrC devant les offres moyennement injustes est significativement plus élevés que celui des participants GrR. De plus, les résultats ne démontrent pas une amplitude FRN significativement plus grande chez les participants GrR comparée à celle chez les participants GrC, et ceci peu importe le type d’offres. De manière congruente avec la littérature, la FRN associée aux offres très injustes et moyennement injustes est plus négative que celle associée aux offres justes. Toutefois, dans le cadre de la présente étude, ce résultat sur la FRN a été observé uniquement pour le GrC. Enfin, que ce soit en réponse à des offres très injustes ou moyennement injustes, les résultats ne démontrent pas le rôle modérateur du trait de vengeance dans la relation entre l’amplitude de la FRN et le taux de rejet d’offres monétaires. L’effet de groupe observé sur le taux de rejet des offres moyennement injustes suggère que les personnes en colère résolvent leur conflit cognitif davantage en outre-passant leurs intérêts personnels monétaires comparativement aux personnes qui vivent de la rancune. Ces résultats suggèrent aussi que, contrairement aux individus en état de colère qui perçoivent les offres justes d’une façon différente des autres types d’offres, les individus vivant de la rancune perçoivent les offres justes, moyennement injustes et très injustes de la même façon. Il est possible de croire que l’état de rancune augmente la sensibilité à l’injustice envers des offres qui normalement devrait être perçues comme différentes. Des limites méthodologiques peuvent possiblement expliquer l’absence d’effet de modération du trait de vengeance. / Vengeance refers to the attempt to hurt or harm someone who has caused us harm through their wrong. While revenge refers to action, the desire for vengeance refers to the emotion that motivates revenge. Anger is an emotion felt when we suffer from a perceived or actual harm (sudden interference in the pursuit of an important goal for us), while resentment is an emotion that is aroused by the perception of having or the fact of having actually suffered from a wrong (harm that is responsibly inflicted by an individual on a victim). These definitions of anger and resentment can be operationalized by provoking participants in such a way that they perceive it as accidental (without wrong) or personal (with wrong); the first provocation would induce an emotional state of anger while the second would induce a state of resentment. Past studies have demonstrated the effect of anger on the rejection rate of unfair and mid-value offers compared to fair offers during an economic decision-making task such as the Ultimatum Game (UG), as well as on the amplitude of Feedback-Related Negativity (FRN), an event-related potential that becomes more pronounced during negative feedback associated with unfavorable outcomes (e.g., incorrect responses or monetary losses). These prior studies suggest that anger would increase the negative affective evaluation associated with unfair and mid-value offers and vengeance behaviors associated with rejection rates. The role of emotions in vengeance raises the question of whether their influence is transmitted directly into revenge behaviors. Trait vengeance refers to the dispositional tendency to maintain positive attitudes toward revenge and to seek it in response to provocations. Previous studies demonstrated that trait negative affect moderated the relationship between state negative affect and FRN magnitude. There is a gap in our knowledge about the role of trait vengeance on the relationship between the FRN amplitude and the rejection rate of monetary offers. The first objective of the current study is to compare the effects of anger to those of resentment on the rejection rate of fair, mid-value and unfair offers as well as on the FRN amplitude during the UG. The second objective is to verify the moderating role of trait vengeance on the relationship between FRN amplitude and the rejection rate in response to unfair and mid-value offers. Two experimental groups were created: a group primed with a human provocation without wrong (Unwronged) and a second group primed with a human provocation with wrong (Wronged). The first group underwent anger induction through a human provocation without wrong while performing a creativity task. During the same creativity task, participants in the second group were subjected to a resentment induction through a human provocation with wrong. Next, participants were asked to participate in the UG, in which they had to accept or reject unfair, mid-value, and fair offers proposed by a fictitious participant. In addition to the analysis of the rejection rate, the electroencephalographic (EEG) signal was quantified and then analyzed on the FRN amplitude with the aim of serving as a proxy for the perception of injustice and the level of complexity of decision-making based on the experimental groups and the type of offers. Contrary to what was expected, the results indicate that the rejection rate of the Unwronged group in response to mid-value offers is significantly higher than the Wronged group. Furthermore, the results do not demonstrate a significantly greater FRN amplitude in the Wronged group compared to the Unwronged group, regardless of the type of offers. In accordance with the literature, the FRNs associated with unfair and mid-value offers are more negative compared to the FRN associated with fair offers. However, in the context of the present study, this result on FRN was observed only for the Unwronged group. Finally, whether in response to unfair or mid-value offers, the results do not demonstrate the moderating role of the trait vengeance in the relationship between the FRN amplitude and the rejection rate. The group effect observed on the rejection rate of mid-value offers suggests that angry participants resolve their cognitive conflict more by overriding their personal monetary interests compared to participants who feel resentment. These results also suggest that, unlike individuals in a state of anger who perceive fair offers in a different way from other types of offers, individuals feeling resentment perceive fair, mid-value and unfair offers in the same way. It is possible to believe that the state of resentment increases sensitivity to injustice towards offers that should normally be perceived as different. Methodological limitations can possibly explain the lack of moderation effect of the trait vengeance.

Nesta dissertação é explorado o comportamento emergente de uma população heterogênea de jogadores negociando segundo o jogo do ultimato: dois jogadores recebem uma oferta; um deles (o proponente) propõe a sua divisão, enquanto o outro jogador (o aceitador) pode aceitar ou rejeitar a proposta. A rejeição é prejudicial a ambos jogadores, pois nenhum deles recebe sua parcela dos possíveis ganhos. Neste contexto, o ganho e seus momentos são calculados a partir de métodos analíticos simples e várias simulações computacionais corroboram os resultados obtidos. Também são analisadas as flutuações estatísticas da distribuição do ganho. Além disso, é apresentada uma abordagem simples evolucionária que considera mudanças em estratégias baseadas em ganhos anteriores. Para este caso, é demonstrado que o tempo médio de permanência (idade) de uma estratégia de uma população de "justos" convergepara um valor constante enquanto t se aproxima do ∞ e o cutoff médio decai segundouma lei de potência em tempos altos, após uma queda inicial. Também foram observadas transições entre comportamentos de alto e baixo ganho. Adicionalmente foi estudadauma versão espacial desse modelo. Para tanto são consideradosjogadores interagindo com seus primeiros vizinhos em reticulados 2D de acordo com duas dinâmicas estocáticas: (1) morte e nascimento com amostragem seletiva (MNAS), (2) Gibbs sampling sobre a vizinhança (GS). Estes resultados trazem importantes considerações sobre o projeto de simulaçõesno contexto da teoria dos jogos evolucionários, em particular na simulação dos aspectos relevantes quando modelando grandes populações. / Weexplore the emergent behavior of a heterogeneous population of players negotiating via an ultimatum game: two players are offered a gift; one of them (the proposer) suggestshow to divide the offer while the other player (the responder) can either agree or reject the deal. Rejection is detrimental to both players as it results in no eamings. In this context, the payoff and its moments are calculated from simple analytical methods and several computer simulations corroborate the obtained results. Wealso analyze statistical fluctuationson payoff distribution. In addition,we present a simple evolutionaryapproach that considers changes in strategies based on previous eamings. For this case, we show that average permanence time (age) in a strategy of a fair population converges to a constant value when t approaches ∞ and the cutoff average decays as a power law for large times after a initial deterministic slip. We have also observed transitions between highlow payoffbehaviors. Additionallywe studied a spatial version ofthis model. For this we consider players interacting with their nearest neighbors in 2D lattices according to two different stochastic dynamics: (1) Death and birth with selective sampling (MNAS), (2) Gibbs sampling on neighborhood (GS) Webelieve that these results can bring important considerationsto the design of simulations in the context ofthe evolutionary game theory, in particular in the simulation of relevant features when modeling large populations.

No description available.

Nesta dissertação é explorado o comportamento emergente de uma população heterogênea de jogadores negociando segundo o jogo do ultimato: dois jogadores recebem uma oferta; um deles (o proponente) propõe a sua divisão, enquanto o outro jogador (o aceitador) pode aceitar ou rejeitar a proposta. A rejeição é prejudicial a ambos jogadores, pois nenhum deles recebe sua parcela dos possíveis ganhos. Neste contexto, o ganho e seus momentos são calculados a partir de métodos analíticos simples e várias simulações computacionais corroboram os resultados obtidos. Também são analisadas as flutuações estatísticas da distribuição do ganho. Além disso, é apresentada uma abordagem simples evolucionária que considera mudanças em estratégias baseadas em ganhos anteriores. Para este caso, é demonstrado que o tempo médio de permanência (idade) de uma estratégia de uma população de "justos" convergepara um valor constante enquanto t se aproxima do ∞ e o cutoff médio decai segundouma lei de potência em tempos altos, após uma queda inicial. Também foram observadas transições entre comportamentos de alto e baixo ganho. Adicionalmente foi estudadauma versão espacial desse modelo. Para tanto são consideradosjogadores interagindo com seus primeiros vizinhos em reticulados 2D de acordo com duas dinâmicas estocáticas: (1) morte e nascimento com amostragem seletiva (MNAS), (2) Gibbs sampling sobre a vizinhança (GS). Estes resultados trazem importantes considerações sobre o projeto de simulaçõesno contexto da teoria dos jogos evolucionários, em particular na simulação dos aspectos relevantes quando modelando grandes populações. / Weexplore the emergent behavior of a heterogeneous population of players negotiating via an ultimatum game: two players are offered a gift; one of them (the proposer) suggestshow to divide the offer while the other player (the responder) can either agree or reject the deal. Rejection is detrimental to both players as it results in no eamings. In this context, the payoff and its moments are calculated from simple analytical methods and several computer simulations corroborate the obtained results. Wealso analyze statistical fluctuationson payoff distribution. In addition,we present a simple evolutionaryapproach that considers changes in strategies based on previous eamings. For this case, we show that average permanence time (age) in a strategy of a fair population converges to a constant value when t approaches ∞ and the cutoff average decays as a power law for large times after a initial deterministic slip. We have also observed transitions between highlow payoffbehaviors. Additionallywe studied a spatial version ofthis model. For this we consider players interacting with their nearest neighbors in 2D lattices according to two different stochastic dynamics: (1) Death and birth with selective sampling (MNAS), (2) Gibbs sampling on neighborhood (GS) Webelieve that these results can bring important considerationsto the design of simulations in the context ofthe evolutionary game theory, in particular in the simulation of relevant features when modeling large populations.

Nesta dissertação é explorado o comportamento emergente de uma população heterogênea de jogadores negociando segundo o jogo do ultimato: dois jogadores recebem uma oferta; um deles (o proponente) propõe a sua divisão, enquanto o outro jogador (o aceitador) pode aceitar ou rejeitar a proposta. A rejeição é prejudicial a ambos jogadores, pois nenhum deles recebe sua parcela dos possíveis ganhos. Neste contexto, o ganho e seus momentos são calculados a partir de métodos analíticos simples e várias simulações computacionais corroboram os resultados obtidos. Também são analisadas as flutuações estatísticas da distribuição do ganho. Além disso, é apresentada uma abordagem simples evolucionária que considera mudanças em estratégias baseadas em ganhos anteriores. Para este caso, é demonstrado que o tempo médio de permanência (idade) de uma estratégia de uma população de "justos" convergepara um valor constante enquanto t se aproxima do ∞ e o cutoff médio decai segundouma lei de potência em tempos altos, após uma queda inicial. Também foram observadas transições entre comportamentos de alto e baixo ganho. Adicionalmente foi estudadauma versão espacial desse modelo. Para tanto são consideradosjogadores interagindo com seus primeiros vizinhos em reticulados 2D de acordo com duas dinâmicas estocáticas: (1) morte e nascimento com amostragem seletiva (MNAS), (2) Gibbs sampling sobre a vizinhança (GS). Estes resultados trazem importantes considerações sobre o projeto de simulaçõesno contexto da teoria dos jogos evolucionários, em particular na simulação dos aspectos relevantes quando modelando grandes populações. / Weexplore the emergent behavior of a heterogeneous population of players negotiating via an ultimatum game: two players are offered a gift; one of them (the proposer) suggestshow to divide the offer while the other player (the responder) can either agree or reject the deal. Rejection is detrimental to both players as it results in no eamings. In this context, the payoff and its moments are calculated from simple analytical methods and several computer simulations corroborate the obtained results. Wealso analyze statistical fluctuationson payoff distribution. In addition,we present a simple evolutionaryapproach that considers changes in strategies based on previous eamings. For this case, we show that average permanence time (age) in a strategy of a fair population converges to a constant value when t approaches ∞ and the cutoff average decays as a power law for large times after a initial deterministic slip. We have also observed transitions between highlow payoffbehaviors. Additionallywe studied a spatial version ofthis model. For this we consider players interacting with their nearest neighbors in 2D lattices according to two different stochastic dynamics: (1) Death and birth with selective sampling (MNAS), (2) Gibbs sampling on neighborhood (GS) Webelieve that these results can bring important considerationsto the design of simulations in the context ofthe evolutionary game theory, in particular in the simulation of relevant features when modeling large populations.