Cognition in Spatial Dispersion Games

In common-interest spatial-dispersion games the agents common goal is to choose distinct locations.We experimentally investigate the role of cognition in such games and compare it with the role of cognition in spatial matching games. In our setup cognition matters because agents may be differentially aware of the dispersion opportunities that are created by the history of the game.We ask whether cognitive constraints limit the agents ability to achieve dispersion and, if there is dispersion, whether these constraints affect the mode by which agents achieve dispersion.Our main finding is that strategic interaction magnifies the role of cognitive constraints.Specifically, with cognitive constraints, pairs of agents fail to solve a dispersion problem that poses little or no problem for individual agents playing against themselves.When we remove the cognitive constraints in our design, pairs of agents solve the same problem just as well as individuals do.In addition, we find that when playing against themselves agents do not change the mode by which they solve the dispersion problem when our design removes the cognitive constraints.noncooperative games;laboratory group behavior

Cognition in Spatial Dispersion Games

In common-interest spatial-dispersion games the agents common goal is to choose distinct locations.We experimentally investigate the role of cognition in such games and compare it with the role of cognition in spatial matching games. In our setup cognition matters because agents may be differentially aware of the dispersion opportunities that are created by the history of the game.We ask whether cognitive constraints limit the agents ability to achieve dispersion and, if there is dispersion, whether these constraints affect the mode by which agents achieve dispersion.Our main finding is that strategic interaction magnifies the role of cognitive constraints.Specifically, with cognitive constraints, pairs of agents fail to solve a dispersion problem that poses little or no problem for individual agents playing against themselves.When we remove the cognitive constraints in our design, pairs of agents solve the same problem just as well as individuals do.In addition, we find that when playing against themselves agents do not change the mode by which they solve the dispersion problem when our design removes the cognitive constraints

Decision Support System for Urbanization of the Northern Part of the Volga-Akhtuba Floodplain (Russia) on the Basis of Interdisciplinary Computer Modeling

There is a computer decision support system (CDSS) for urbanization of the northern part of the Volga-Akhtuba floodplain. This system includes subsystems of cognitive and game-theoretic analysis, geoinformation and hydrodynamic simulations. The paper presents the cognitive graph, two-level and three-level models of hierarchical games for the cases of uncontrolled and controlled development of the problem situation. We described the quantitative analysis of the effects of different strategies for the spatial distribution of the urbanized territories. For this reason we conducted the territory zoning according to the level of negative consequences of urbanization for various agents. In addition, we found an analytical solution for games with the linear dependence of the average flooded area on the urbanized area. We numerically computed a game equilibrium for dependences derived from the imitational geoinformation and hydrodynamic modeling of flooding. As the result, we showed that the transition to the three-level management system and the implementation of an optimal urbanization strategy minimize its negative consequences.Comment: 14 pages, 5 figures; Conference: Creativity in Intelligent Technologies and Data Science. CIT&DS 201

Who should be called to the lab? A comprehensive comparison of students and non-students in classic experimental games

This study compares the behavior of students and non-students in a number of classic experimental games. We find that students are more likely to behave as homo-economicus agents than non-students in games involving other-regarding preferences (Dictator Game, Trust Game and Public Good Game). These differences persist even when controlling for demographics, cognitive ability and risk preferences. In games that do not engage other-regarding preferences (Beauty-contest and Second-price Auction) there is limited evidence of differences in behaviour between subject pools. In none of the five games is there evidence of significant differences in comprehension between students and non-students. Within subject analyses indicate that students are highly consistent in their other-regarding preferences while non-student subjects are inconsistent across other-regarding games. Our findings suggest that experiments using students will provide a lower bound estimate of other-regardedness in the general population while exaggerating the stability of other-regarding preferences.lab experiments, convenience samples, other-regarding preferences, consistency

A cognitive hierarchy model of learning in networks

This paper proposes a method for estimating a hierarchical model of bounded rationality in games of learning in networks. A cognitive hierarchy comprises a set of cognitive types whose behavior ranges from random to substantively rational. SpeciÖcally, each cognitive type in the model corresponds to the number of periods in which economic agents process new information. Using experimental data, we estimate type distributions in a variety of task environments and show how estimated distributions depend on the structural properties of the environments. The estimation results identify signiÖcant levels of behavioral hetero-geneity in the experimental data and overall conÖrm comparative static conjectures on type distributions across task environments. Surprisingly, the model replicates the aggregate pat-terns of the behavior in the data quite well. Finally, we found that the dominant type in the data is closely related to Bayes-rational behavior

Learning backward induction: a neural network agent approach

This paper addresses the question of whether neural networks (NNs), a realistic cognitive model of human information processing, can learn to backward induce in a two-stage game with a unique subgame-perfect Nash equilibrium. The NNs were found to predict the Nash equilibrium approximately 70% of the time in new games. Similarly to humans, the neural network agents are also found to suffer from subgame and truncation inconsistency, supporting the contention that they are appropriate models of general learning in humans. The agents were found to behave in a bounded rational manner as a result of the endogenous emergence of decision heuristics. In particular a very simple heuristic socialmax, that chooses the cell with the highest social payoff explains their behavior approximately 60% of the time, whereas the ownmax heuristic that simply chooses the cell with the maximum payoff for that agent fares worse explaining behavior roughly 38%, albeit still significantly better than chance. These two heuristics were found to be ecologically valid for the backward induction problem as they predicted the Nash equilibrium in 67% and 50% of the games respectively. Compared to various standard classification algorithms, the NNs were found to be only slightly more accurate than standard discriminant analyses. However, the latter do not model the dynamic learning process and have an ad hoc postulated functional form. In contrast, a NN agent’s behavior evolves with experience and is capable of taking on any functional form according to the universal approximation theorem.

Leadership and Overcoming Coordination Failure with Asymmetric Costs

We study how the heterogeneity of agents affects the extent to which changes in financial incentives can pull a group out of a situation of coordination failure. We focus on the connections between cost asymmetries and leadership. Experimental subjects interact in groups of four in a series of weak-link games. The treatment variable is the distribution of high and low effort cost across subjects. We present data for one, two and three low-cost subjects as well as control sessions with symmetric costs. The overall pattern of coordination improvement is common across treatments. Early coordination improvements depend on the distribution of high and low effort costs across subjects, but these differences disappear with time. We find that initial leadership in overcoming coordination failure is not driven by low-cost subjects but by subjects with the most frequent cost. This conformity effect can be due to a kind of group identity or to the cognitive simplicity of acting with identical others.Experiments, Coordination, Organizational change, Heterogeneous agents, Leadership