Bounded Rationality and Repeated Network Formation

We define a finite-horizon repeated network formation game with consent, and study the differences induced by different levels of individual rationality. We prove that perfectly rational players will remain unconnected at the equilibrium, while nonempty equilibrium networks may form when, following Neyman (1985), players are assumed to behave as finite automata. We define two types of equilibria, namely the Repeated Nash Network (RNN), in which the same network forms at each period, and the Repeated Nash Equilibrium (RNE), in which different networks may form. We state a sufficient condition under which a given network may be implemented as a RNN. Then, we provide structural properties of RNE. For instance, players may form totally different networks at each period, or the networks within a given RNE may exhibit a total order relationship. Finally we investigate the question of efficiency for both Bentham and Pareto criteria.Repeated Network Formation Game, Two-sided Link Formation Costs, Bounded Rationality, Automata

Network Formation with Adaptive Agents

In this paper, a reinforcement learning version of the connections game first analysed by Jackson and Wolinsky is presented and compared with benchmark results of fully informed and rational players. Using an agent-based simulation approach, the main nding is that the pattern of reinforcement learning process is similar, but does not fully converge to the benchmark results. Before these optimal results can be discovered in a learning process, agents often get locked in a state of random switching or early lock-in.agent-based computational economics; strategic network formation; network games; reinforcement learning

Computer Science and Game Theory: A Brief Survey

There has been a remarkable increase in work at the interface of computer science and game theory in the past decade. In this article I survey some of the main themes of work in the area, with a focus on the work in computer science. Given the length constraints, I make no attempt at being comprehensive, especially since other surveys are also available, and a comprehensive survey book will appear shortly.Comment: To appear; Palgrave Dictionary of Economic

Bounded Rationality

The observation of the actual behavior by economic decision makers in the lab and in the field justifies that bounded rationality has been a generally accepted assumption in many socio-economic models. The goal of this paper is to illustrate the difficulties involved in providing a correct definition of what a rational (or irrational) agent is. In this paper we describe two frameworks that employ different approaches for analyzing bounded rationality. The first is a spatial segregation set-up that encompasses two optimization methodologies: backward induction and forward induction. The main result is that, even under the same state of knowledge, rational and non-rational agents may match their actions. The second framework elaborates on the relationship between irrationality and informational restrictions. We use the beauty contest (Nagel, 1995) as a device to explain this relationship.Behavioral economics, bounded rationality, partial information

Topology of large-scale engineering problem-solving networks

The last few years have led to a series of discoveries that uncovered statistical properties that are common to a variety of diverse real-world social, information, biological, and technological networks. The goal of the present paper is to investigate the statistical properties of networks of people engaged in distributed problem solving and discuss their significance. We show that problem-solving networks have properties ~sparseness, small world, scaling regimes! that are like those displayed by information, biological, and technological networks. More importantly, we demonstrate a previously unreported difference between the distribution of incoming and outgoing links of directed networks. Specifically, the incoming link distributions have sharp cutoffs that are substantially lower than those of the outgoing link distributions ~sometimes the outgoing cutoffs are not even present!. This asymmetry can be explained by considering the dynamical interactions that take place in distributed problem solving and may be related to differences between each actor’s capacity to process information provided by others and the actor’s capacity to transmit information over the network. We conjecture that the asymmetric link distribution is likely to hold for other human or nonhuman directed networks when nodes represent information processing and using elements