An extended reinforcement algorithm for estimation of human behaviour in experimental congestion games

The paper reports simulations applied on two similar congestion games: the first is the classical minority game. The second one is an asymmetric variation of the minority game with linear payoff functions. For each game, simulation results based on an extended reinforcement algorithm are compared with real experimental statistics. It is shown that the extension of the reinforcement model is essential for fitting the experimental data and estimating the player's behaviour

Successful strategies in repeated minority games

The minority game is an important example of a non-cooperative n-person game, which can be applied on different situations with social and economic contexts. We analysed the minority game as an elementary traffic scenario in which human participants had to choose 100 times between a road A and a road B. In each period, the road, which was chosen by the minority of players won. At first view, there seems to be no outstandingly advisable strategy for the participants to enhance their payoffs because both roads have the same properties. However, an important observation is that the number of road changes of a participant is negatively correlated to his/her cumulative payoff. On average, subjects with high numbers of road changes received less money than participants who stoically chose the same road. Furthermore one could increase the coordination of the players by providing the players distribution on both roads in the last period

Experiments and Simulations on Day-to-Day Route Choice-Behaviour

The paper reports laboratory experiments on a day-to-day route choice game with two routes. Subjects had to choose between a main road M and a side road S. The capacity was greater for the main road. 18 subjects participated in each session. In equilibrium the number of subjects is 12 on M and 6 on S. Two treatments with 6 sessions each were run at the Laboratory of Experimental Economics at Bonn University using RatImage. Feedback was given in treatment I only about own travel time and in treatment II on travel time for M and S. Money payoffs increase with decreasing time. The main results are as follows. 1. Mean numbers on M and S are very near to the equilibrium. 2. Fluctuations persist until the end of the sessions in both treatments. 3. Fluctuations are smaller under treatment II .The effect is small but significant. 4. The total number of changes is significantly greater in treatment I. 5. Subjects’ road changes and payoffs are negatively correlated in all sessions. 6. A direct response mode reacts with more changes for bad payoffs whereas a contrary response mode shows opposite reactions. Both response modes can be observed. 7. The simulation of an extended payoff sum learning model closely fits the main results of the statistical evaluation of the data.travel behaviour research, information in intelligent transportation systems, day-to-day route choice, laboratory experiments, payoff sum model

Natural groups and economic characteristics as driving forces of wage discrimination

We investigate whether the origin of an employee provides different motives for wage discrimination in gift-exchange experiments with students and migrant workers in China. In a lab and an internet experiment, subjects in the role of employers can condition their wages on the employees' home provinces. The resulting systematic differences in wages can be linked to natural groups and economic characteristics of the provinces. In-group favoritism increases wages for employees who share the same origin as the employer, while an increased probability of being matched with an employee with a different ethnicity reduces wages. Furthermore, wages in the laboratory increase with the actual wage level in the employees׳ home province. Nevertheless, employees' effort is not influenced by these variables; only the wage paid in the experiment influences effort

At the mercy of a prisoner three dictator experiments

We test male juvenile prisoners on a dictator game with another anonymous co-prisoner as recipient. Prisoners give more than students, but less than non-students of their age. They give more to a charity than to another prisoner. In one of two experiments, those convicted for violent crime give more than those convicted for property crime

Learning in experimental games

In this paper, we introduce two new learning models: action-sampling learning and impulse-matching learning. These two models, together with the models of self-tuning EWA and reinforcement learning, are applied to 12 different 2 X 2 games and their results are compared with the results from experimental data. We test whether the models are capable of replicating the aggregate distribution of behavior, as well as correctly predicting individualsʼ round-by-round behavior. Our results are two-fold: while the simulations with impulse-matching and action-sampling learning successfully replicate the experimental data on the aggregate level, individual behavior is best described by self-tuning EWA. Nevertheless, impulse-matching learning has the second-highest score for the individual data. In addition, only self-tuning EWA and impulse-matching learning lead to better round-by-round predictions than the aggregate frequencies, which means they adjust their predictions correctly over time

Testing (beliefs about) social preferences: evidence from an experimental coordination game

We report experimental results on a simple coordination game in which two players can coordinate either on an equal distribution of payoffs or on a Pareto superior but unequal distribution of payoffs. We find that the higher the difference in individual payoffs, the less likely is a successful coordination on the Pareto superior distribution. While this is well in line with the recent models of inequity aversion, our results are best explained not by a preference for equality per se but rather by the belief that the opponent has such a preference

Generalized impulse balance: an experimental test for a class of 3 X 3 games

In this paper, we introduce a generalized version of impulse balance equilibrium. The stationary concept is applied to 3 × 3 games based on the Bailiff and Poacher Game (Selten, 1991) and its predictive success is experimentally tested against the one of Nash equilibrium. Experiments with 26 different games were conducted; 12 games with completely mixed Nash equilibria and 14 games with partially mixed Nash equilibria. In all the games, generalized impulse balance yields predictions that are closer to the data than the ones of Nash equilibrium. Overall, generalized impulse balance has a significantly higher predictive success than Nash equilibrium

Bargaining over perfect complements owned separately: with experimental test

This paper considers the situation in which two perfect complements belong to different owners. We calculate the Bayesian–Nash equilibrium in the mechanism of k + 1 − price bargaining with private value, and did experiment to test the theory

Route choice in the presence of a toll road: The role of pre-trip information and learning

Choosing a route is a complex task, especially since the roads’ capacities are limited and road users non-cooperatively seek to optimize their own trip. This article present the results of three in-laboratory route choice experiments. In all experiments the participants had to choose repeatedly between a high-capacity toll-road and a toll-free main road. We investigate the role of pre-trip information on the resulting route usage dynamics. Besides the absence of a stable equilibrium point (Wardrop’s User Equilibrium), we found that the participants improve their decisions over the course of time as a result of learning. Additional information appears only useful if only a limited number of participants possess such information. Moreover, we found gender-related differences in the observed road usage patterns: female participants were more likely to choose the toll road than male participants