Behavioral Experiments on a Network Formation Game

We report on an extensive series of behavioral experiments in which 36 human subjects collectively build a communication network over which they must solve a competitive coordination task for monetary compensation. There is a cost for creating network links, thus creating a tension between link expenditures and collective and individual incentives. Our most striking finding is the poor performance of the subjects, especially compared to our long series of prior experiments. We demonstrate that the subjects built difficult networks for the coordination task, and compare the structural properties of the built networks to standard generative models of social networks. We also provide extensive analysis of the individual and collective behavior of the subjects, including free riding and factors influencing edge purchasing decisions

Coordination in Networks Formation: Experimental Evidence on Learning and Salience

We present experiments on repeated non-cooperative network formation games, based on Bala and Goyal (2000). We treat the one-way and the two-ways flow models, each for high and low link costs. The models show both multiple equilibria and coordination problems. We conduct experiments under various conditions which control for salient labeling and learning dynamics. Contrary to previous experiments, we find that coordination on non-empty Strict Nash equilibria is not an easy task for subjects to achieve, even in the mono-directional model where the Strict Nash equilibria is a wheel. We find that salience significantly helps coordination, but only when subjects are pre-instructed to think of the wheel network as a reasonable way to play the networking game. Evidence on learning behavior provides support for subjects choosing strategies consistent with various learning rules, which include as the main ones Reinforcement and Fictitious Play.Experiments, Networks, Behavioral game theory, Salience, Learning dynamics

Complexity of Networking: An Experimental Study of the Network Hawk Dove Game

Complexity of strategies is central for human decision making and attracted interest of different game theorists in the recent years. Nevertheless, behavioral economists have neglected the importance of complexity in their analyses. In this paper, we analyze network formation and action selection in a Hawk Dove Game with focus on complexity aspects. We conduct experiments with three variants of the game which are equivalent from a game theoretic perspective, but differ from a complexity theoretic perspective. Our results show, that complexity of decision making has an impact on the strategies played and that efficiency is higher the less complex the decision problem is

Analyzing Social Network Structures in the Iterated Prisoner's Dilemma with Choice and Refusal

The Iterated Prisoner's Dilemma with Choice and Refusal (IPD/CR) is an extension of the Iterated Prisoner's Dilemma with evolution that allows players to choose and to refuse their game partners. From individual behaviors, behavioral population structures emerge. In this report, we examine one particular IPD/CR environment and document the social network methods used to identify population behaviors found within this complex adaptive system. In contrast to the standard homogeneous population of nice cooperators, we have also found metastable populations of mixed strategies within this environment. In particular, the social networks of interesting populations and their evolution are examined.Comment: 37 pages, uuencoded gzip'd Postscript (1.1Mb when gunzip'd) also available via WWW at http://www.cs.wisc.edu/~smucker/ipd-cr/ipd-cr.htm

Myopically Forward-Looking Agents in a Network Formation Game: Theory and Experimental Evidence

A population of players is considered in which each agent can select her neighbors in order to play a 2x2 Hawk-Dove game with each of them. We design our experiment in continuous time where participants may change their Hawk-Dove action and/or their neighborhood at any point in time. We are interested in the resulting formation of networks and the action distributions. Compared with static Nash equilibrium (e.g., Berninghaus and Vogt, 2004, 2006; Bramoulle, Lopez-Pintado, Goyal, and Vega-Redondo, 2004) and social optimum as theoretical benchmark solutions, subjects seem to employ a more complex, forward-looking thinking. We develop an other benchmark solution, called one-step-ahead stability, that combines forward-looking belief formation with rational response and that fits the data much better.

Agent-Based Computational Economics

Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Starting from initial conditions, specified by the modeler, the computational economy evolves over time as its constituent agents repeatedly interact with each other and learn from these interactions. ACE is therefore a bottom-up culture-dish approach to the study of economic systems. This study discusses the key characteristics and goals of the ACE methodology. Eight currently active research areas are highlighted for concrete illustration. Potential advantages and disadvantages of the ACE methodology are considered, along with open questions and possible directions for future research.Agent-based computational economics; Autonomous agents; Interaction networks; Learning; Evolution; Mechanism design; Computational economics; Object-oriented programming.

Public goods and decay in networks

We propose a simple behavioral model to analyze situations where (1) a group of agents repeatedly plays a public goods game within a network structure and (2) each agent only observes the past behavior of her neighbors, but is affected by the decisions of the whole group. The model assumes that agents are imperfect conditional cooperators, that they infer unobserved contributions assuming imperfect conditional cooperation by others, and that they have some degree of bounded rationality. We show that our model approximates quite accurately regularities derived from public goods game experiments