Is memory in the minority game irrelevant?

Minority games with score-dependent and agent-dependent payoffs

Score-dependent and agent-dependent payoffs of the strategies are introduced into the standard minority game. The intrinsic periodicity is consequently removed, and the stylized facts arise, such as long-range volatility correlations and "fat tails" in the distribution of the returns. The agent dependence of the payoffs is essential in producing the long-range volatility correlations. The new payoffs lead to a better performance in the dynamic behavior nonlocal in time, and can coexist with the inactive strategy. We also observe that the standard deviation sigma2/N is significantly reduced, thus the efficiency of the system is distinctly improved. Based on this observation, we give a qualitative explanation for the long-range volatility correlations.

Incorporating inertia into multiagent systems

We consider a model that demonstrates the crucial role of inertia and stickiness in multiagent systems, based on the minority game. The inertia of an agent is introduced into the game model by allowing agents to apply hypothesis testing when choosing their best strategies, thereby reducing their reactivity toward changes in the environment. We find by extensive numerical simulations that our game shows a remarkable improvement of global cooperation throughout the whole phase space. In other words, the maladaptation behavior due to over-reaction of agents is removed. These agents are also shown to be advantageous over the standard ones, which are sometimes too sensitive to attain a fair success rate. We also calculate analytically the minimum amount of inertia needed to achieve the above improvement. Our calculation is consistent with the numerical simulation results. Finally, we review some related works in the field that show similar behaviors and compare them to our work.

Effects of diversity on multiagent systems: minority games

We consider a version of large population games whose agents compete for resources using strategies with adaptable preferences. The games can be used to model economic markets, ecosystems, or distributed control. Diversity of initial preferences of strategies is introduced by randomly assigning biases to the strategies of different agents. We find that diversity among the agents reduces their maladaptive behavior. We find interesting scaling relations with diversity for the variance and other parameters such as the convergence time, the fraction of fickle agents, and the variance of wealth, illustrating their dynamical origin. When diversity increases, the scaling dynamics is modified by kinetic sampling and waiting effects. Analyses yield excellent agreement with simulations.

Memory is relevant in the symmetric phase of the minority game

Minority game is a simple-mined econophysical model capturing the cooperative behavior among selfish players. Previous investigations, which were based on numerical simulations up to about 100 players for a certain parameter alpha in the range 0.1 < approximately alpha < approximately 1, suggested that memory is irrelevant to the cooperative behavior of the minority game in the so-called symmetric phase. Here using a large scale numerical simulation up to about 3000 players in the parameter range 0.01 < approximately alpha < approximately 1, we show that the mean variance of the attendance in the minority game actually depends on the memory in the symmetric phase. We explain such dependence in the framework of crowd-anticrowd theory. Our findings conclude that one should not overlook the feedback mechanism buried under the correlation in the history time series in the study of minority game.