The Three Versions of the Ultimatum Game

We examine the 1914-1918 creation of the Kingdom of Serbs, Croats and Slovenes as a form of the ultimatum game. The negotiations among the Serbian Cabinet and the yugoslav Committee representatives of the Habsburg Souths Slavs from 1914-1918 exemplify three versions of this game. The first version is a typical (rational choice) type of the ultimatum game in which the receiver is satisfied with any offer by the Proposer. The second version is an instance of behavioral game theory. When the Proposer gives an unfair offer, it provokes an emotional reaction in the receiver who will reject it at the cost of harming themselves. We observe this behavior in the emotional behavior of frano Supilo, a Croat and one of the leaders of the yugoslav Committee. The third version of the behavioral ultimatum game can be observed in the behavior of Serbian Prime minister nikola Pašić who opposed any concessions to the yugoslav Committee, thus giving an ultimatum to the Croat side to accept the Serbian offer or remain with nothing, which was harmful to the Serbian side, too. This example is important because it produces two conclusions. first, historical games are often a mixture of several versions. Second, Proposers, too, can have an emotional reaction and give an offer that can hurt themselves. This aspect of the ultimatum game is less mentioned because it is difficult to simulate in experiments.

Game Awareness: A Questionnaire

This paper deals with one of the possible methodological approaches to an empirical examination of game awareness. Such an outline should enable the gathering of a deeper understanding of individuals’ awareness. The questionnaire is based on a scenario technique, and it is focused on game awareness in situations with possible strategic interactions. The goal is to assess the instrument regarding its reliability and validity. Internal reliability is assessed using Cronbach’s alpha coefficient. A k-nn analysis was used to estimate divergent construct validity and criterion validity, and nonparametric factor analysis was used to estimate convergent construct validity. The questionnaire satisfies the requirements of reliability and validity. Moreover, there is an indication that each of the eight scenarios may be used separately, as they also meet the criteria for reliability and validity. Possible practical and theoretical implications involve questionnaire use as a basis for educational intervention, other instruments’ development, as well as for the collection and publication of behavioral insights about game awareness. Behavioral insights should enrich the theory and incite behavioral game theory models of game awareness and its implications.

M Equilibrium: A Theory of Beliefs and Choices in Games

We introduce a set-valued solution concept, M equilibrium, to capture empirical regularities from over half a century of game theory experiments. We show M equilibrium serves as a meta theory for various models that hitherto were considered unrelated. M equilibrium is empirically robust and, despite being set-valued, falsifiable. Results from a series of experiments that compare M equilibrium to leading behavioral game theory models demonstrate its virtues in predicting observed choices and stated beliefs. Data from experimental games with a unique pure-strategy Nash equilibrium and multiple M equilibria exhibit coordination problems that could not be anticipated through the lens of existing models. (JEL C72, C90, D83)

The pitfalls associated with more intensive engagement in collaborative forums: The role of behavioral spillovers and cognitive load

Polycentric governance systems feature numerous decision-making venues (“forums”) where policy actors repeatedly interact to address a subset of policy problems. Previous studies find that forums where actors dedicate greater time and cognitive resources tend to be perceived as more effective. Drawing on behavioral game theory and the Ecology of Games, we argue that the improvements afforded to any one forum vis-à-vis more intensive participation may come at a cost: lower levels of perceived effectiveness in linked forums. We use survey data collected in the Tampa Bay (FL) and California Delta (CA) water governance systems to examine our contention. Using a series of spatial Durbin models, we find that perceived effectiveness of a given forum is directly impacted by the intensiveness by which actors participate in that forum (positive association). However, there are also behavioral spillovers: the intensity with which actors participate in other forums in the system has indirect negative consequences for perceived forum effectiveness.

Using a Stochastic Agent Model to Optimize Performance in Divergent Interest Tacit Coordination Games

In recent years collaborative robots have become major market drivers in industry 5.0, which aims to incorporate them alongside humans in a wide array of settings ranging from welding to rehabilitation. Improving human–machine collaboration entails using computational algorithms that will save processing as well as communication cost. In this study we have constructed an agent that can choose when to cooperate using an optimal strategy. The agent was designed to operate in the context of divergent interest tacit coordination games in which communication between the players is not possible and the payoff is not symmetric. The agent’s model was based on a behavioral model that can predict the probability of a player converging on prominent solutions with salient features (e.g., focal points) based on the player’s Social Value Orientation (SVO) and the specific game features. The SVO theory pertains to the preferences of decision makers when allocating joint resources between themselves and another player in the context of behavioral game theory. The agent selected stochastically between one of two possible policies, a greedy or a cooperative policy, based on the probability of a player to converge on a focal point. The distribution of the number of points obtained by the autonomous agent incorporating the SVO in the model was better than the results obtained by the human players who played against each other (i.e., the distribution associated with the agent had a higher mean value). Moreover, the distribution of points gained by the agent was better than any of the separate strategies the agent could choose from, namely, always choosing a greedy or a focal point solution. To the best of our knowledge, this is the first attempt to construct an intelligent agent that maximizes its utility by incorporating the belief system of the player in the context of tacit bargaining. This reward-maximizing strategy selection process based on the SVO can also be potentially applied in other human–machine contexts, including multiagent systems.