Finite Neighborhood Binary Games: a Structural Study

The purpose of this study is to present a systematic analysis of the long-term behavior of the agents of an artificial society under varying payoff functions in finite neighborhood binary games. By assuming the linearity of the payoffs of both cooperating and defecting agents, the type of the game is determined by four fundamental parameters. By fixing the values of three of them and systematically varying the fourth one we can observe a transition from Prisoner\'s Dilemma to Leader Game through Chicken and Benevolent Chicken Games. By using agent-based simulation we are able to observe the long-term behavior of the artificial society with different and gradually changing payoff structure. The difference between different games is explored and the effect of the transition from one game to the other on the society is investigated. The results depend on the personality types of the agents. In this study greedy and Pavlovian agents are considered. In the first case, we observe the most significant change in trajectory structure between Prisoner\'s Dilemma and Chicken Games showing significant difference in the behavioral patterns of the agents. Almost no changes can be observed between Benevolent Chicken and Leader Games, and only small change between Chicken and Benevolent Chicken. The trajectories change from always converging to regularly oscillating patterns with systematically altering amplitude and central values. The results are very similar whether the agents consider themselves as members of their neighborhoods or not. With Pavlovian agents no significant difference can be observed between the four games, the trajectories always converge and the limits smoothly and monotonically depend on the value of the varying parameter.Agent-Based Simulation, N-Person Games, Structure Analysis, Equilibrium

Foresighted policy gradient reinforcement learning: solving large-scale social dilemmas with rational altruistic punishment

Many important and difficult problems can be modeled as “social dilemmas”, like Hardin's Tragedy of the Commons or the classic iterated Prisoner's Dilemma. It is well known that in these problems, it can be rational for self-interested agents to promote and sustain cooperation by altruistically dispensing costly punishment to other agents, thus maximizing their own long-term reward. However, self-interested agents using most current multi-agent reinforcement learning algorithms will not sustain cooperation in social dilemmas: the algorithms do not sufficiently capture the consequences on the agent's reward of the interactions that it has with other agents. Recent more foresighted algorithms specifically account for such expected consequences, and have been shown to work well for the small-scale Prisoner's Dilemma. However, this approach quickly becomes intractable for larger social dilemmas. Here, we advance on this work and develop a “teach/learn” stateless foresighted policy gradient reinforcement learning algorithm that applies to Social Dilemma's with negative, unilateral side-payments, in the from of costly punishment. In this setting, the algorithm allows agents to learn the most rewarding actions to take with respect to both the dilemma (Cooperate/Defect) and the “teaching” of other agent's behavior through the dispensing of punishment. Unlike other algorithms, we show that this approach scales well to large settings like the Tragedy of the Commons. We show for a variety of settings that large groups of self-interested agents using this algorithm will robustly find and sustain cooperation in social dilemmas where adaptive agents can punish the behavior of other similarly adaptive agents

Toward a Cognitive Experimental Economics

This paper aims to analyze and exemplify some methodological implications on the way to conduct experiments related to the adoption of a cognitive approach in Economics. Many differences arise in relation to a more traditional way. In fact cognitive economics has strong descriptive attention and aims at beeing closer to reality than the mainstream. Besides the idea of representative agents is questioned. Different kind of experiments, differents analysis and new tools are so required. The paper proposes also some notes on the relation between experimental economics and simulation with artificial agents.cognitive economics, experimental economics, learning

A bibliography of research on behavioral decision processes to 1968

Bibliography of research of human behavioral decision making processes to Jan. 196

About prisoners and dictators: the role of other-self focus, social value orientation, and sterotype primes in shaping cooperative behavior.

Six experiments examined the effects of person factors (i.e., social value orientation and consistency) and situation factors (i.e., stereotype primes) on cooperative behavior in various experimental games. Results indicated that the main and joint influences of person and situation factors on cooperative choices depend on the nature of the game (i.e., prisoner's dilemma or dictator game). Social value orientation, consistency, and primes affect cooperative behavior only in a dictator game, while these factors also lead to rumination about partner's behavioral intentions and personality (and therefore to different cooperative choices) in a prisoner's dilemma game. Differences between these games were explained in terms of the impact they have on other- and self-focus.Choice; Consistency; Dictator game; Effects; Factors; Prisoner's dilemma game; Social Value Orientation; Stereotype Priming; Value;

Parasites may help stabilize cooperative relationships

Background: The persistence of cooperative relationships is an evolutionary paradox; selection should favor those individuals that exploit their partners (cheating), resulting in the breakdown of cooperation over evolutionary time. Our current understanding of the evolutionary stability of mutualisms (cooperation between species) is strongly shaped by the view that they are often maintained by partners having mechanisms to avoid or retaliate against exploitation by cheaters. In contrast, we empirically and theoretically examine how additional symbionts, specifically specialized parasites, potentially influence the stability of bipartite mutualistic associations. In our empirical work we focus on the obligate mutualism between fungus-growing ants and the fungi they cultivate for food. This mutualism is exploited by specialized microfungal parasites (genus Escovopsis) that infect the ant's fungal gardens. Using sub-colonies of fungus-growing ants, we investigate the interactions between the fungus garden parasite and cooperative and experimentally-enforced uncooperative ("cheating") pairs of ants and fungi. To further examine if parasites have the potential to help stabilize some mutualisms we conduct Iterative Prisoner's Dilemma (IPD) simulations, a common framework for predicting the outcomes of cooperative/non-cooperative interactions, which incorporate parasitism as an additional factor. Results: In our empirical work employing sub-colonies of fungus-growing ants, we found that Escovopsis-infected sub-colonies composed of cheating populations of ants or fungi lost significantly more garden biomass than sub-colonies subjected to infection or cheating (ants or fungi) alone. Since the loss of fungus garden compromises the fitness of both mutualists, our findings suggest that the potential benefit received by the ants or fungi for cheating is outweighed by the increased concomitant cost of parasitism engendered by non-cooperation (cheating). IPD simulations support our empirical results by confirming that a purely cooperative strategy, which is unsuccessful in the classic IPD model, becomes stable when parasites are included. Conclusion: Here we suggest, and provide evidence for, parasitism being an external force that has the potential to help stabilize cooperation by aligning the selfish interests of cooperative partners in opposition to a common enemy. Specifically, our empirical results and IPD simulations suggest that when two mutualists share a common enemy selection can favor cooperation over cheating, which may help explain the evolutionary stability of some mutualisms