Boolean Game on Scale-free Networks

Inspired by the local minority game, we propose a network Boolean game and investigate its dynamical properties on scale-free networks. The system can self-organize to a stable state with better performance than random choice game, although only the local information is available to the agent. By introducing the heterogeneity of local interactions, we find the system has the best performance when each agent's interaction frequency is linear correlated with its information capacity. Generally, the agents with more information gain more than those with less information, while in the optimal case, each agent almost has the same average profit. In addition, we investigate the role of irrational factor and find an interesting symmetrical behavior.Comment: 12 pages and 6 figure

Multiplpe Choice Minority Game With Different Publicly Known Histories

In the standard Minority Game, players use historical minority choices as the sole public information to pick one out of the two alternatives. However, publishing historical minority choices is not the only way to present global system information to players when more than two alternatives are available. Thus, it is instructive to study the dynamics and cooperative behaviors of this extended game as a function of the global information provided. We numerically find that although the system dynamics depends on the kind of public information given to the players, the degree of cooperation follows the same trend as that of the standard Minority Game. We also explain most of our findings by the crowd-anticrowd theory.Comment: Extensively revised, to appear in New J Phys, 7 pages with 4 figure

Self-organized Boolean game on networks

A model of Boolean game with only one free parameter $p$ that denotes the strength of herd behavior is proposed where each agent acts according to the information obtained from his neighbors in network and those in the minority are rewarded. The simulation results indicate that the dynamic of system is sensitive to network topology, where the network of larger degree variance, i.e. the system of greater information heterogeneity, leads to less system profit. The system can self-organize to a stable state and perform better than random choice game, although only the local information is available to the agents. In addition, in heterogeneity networks, the agents with more information gain more than those with less information for a wide extent of herd strength $p$.Comment: 5 pages, 5 eps figure

Adaptive Dynamics for Interacting Markovian Processes

Dynamics of information flow in adaptively interacting stochastic processes is studied. We give an extended form of game dynamics for Markovian processes and study its behavior to observe information flow through the system. Examples of the adaptive dynamics for two stochastic processes interacting through matching pennies game interaction are exhibited along with underlying causal structure

The Simulation of Financial Markets by Agent-Based Mix-Game Models

This paper studies the simulation of financial markets using an agent-based mix-game model which is a variant of the minority game (MG). It specifies the spectra of parameters of mix-game models that fit financial markets by investigating the dynamic behaviors of mix-game models under a wide range of parameters. The main findings are (a) in order to approach efficiency, agents in a real financial market must be heterogeneous, boundedly rational and subject to asymmetric information; (b) an active financial market must be dominated by agents who play a minority game; otherwise, the market would die; (c) the system could be stable if agents who play a majority game have a faster learning rate than those who play a minority game; otherwise, the system could be unstable. The paper then induces the rules for simulating financial markets with mix-game models and gives an example. Finally, the appendix of this paper presents background information about \'El Farol bar\', MG and mix-games.Financial Markets, Simulation, Minority Game, Mix-Game

Quantum Games and Programmable Quantum Systems

Attention to the very physical aspects of information characterizes the current research in quantum computation, quantum cryptography and quantum communication. In most of the cases quantum description of the system provides advantages over the classical approach. Game theory, the study of decision making in conflict situation has already been extended to the quantum domain. We would like to review the latest development in quantum game theory that is relevant to information processing. We will begin by illustrating the general idea of a quantum game and methods of gaining an advantage over "classical opponent". Then we review the most important game theoretical aspects of quantum information processing. On grounds of the discussed material, we reason about possible future development of quantum game theory and its impact on information processing and the emerging information society. The idea of quantum artificial intelligence is explained.