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Irrelevance of memory in the minority game  [PDF]
Andrea Cavagna
Physics , 1998, DOI: 10.1103/PhysRevE.59.R3783
Abstract: By means of extensive numerical simulations we show that all the distinctive features of the minority game introduced by Challet and Zhang (1997), are completely independent from the memory of the agents. The only crucial requirement is that all the individuals must posses the same information, irrespective of the fact that this information is true or false.
Broken ergodicity and memory in the minority game  [PDF]
J. A. F. Heimel,A. De Martino
Quantitative Finance , 2001, DOI: 10.1088/0305-4470/34/40/103
Abstract: We study the dynamics of the `batch' minority game with market-impact correction using generating functional techniques to carry out the quenched disorder average. We find that the assumption of weak long-term memory, which one usually makes in order to calculate ergodic stationary states, breaks down when the persistent autocorrelation becomes larger than c_c=0.772... We show that this condition, remarkably, coincides with the AT-line found in an earlier static calculation. This result suggests a new scenario for ergodicity breaking in disordered systems.
Memory is relevant in the symmetric phase of the minority game  [PDF]
K. H. Ho,W. C. Man,F. K. Chow,H. F. Chau
Physics , 2004, DOI: 10.1103/PhysRevE.71.066120
Abstract: 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 $0.1 \lesssim \alpha \lesssim 1$, 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 $0.01 \lesssim \alpha \lesssim 1$, 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.
Self organization in a minority game: the role of memory and a probabilistic approach  [PDF]
E. Burgos,Horacio Ceva
Physics , 2000, DOI: 10.1016/S0378-4371(00)00292-2
Abstract: A minority game whose strategies are given by probabilities p, is replaced by a 'simplified' version that makes no use of memories at all. Numerical results show that the corresponding distribution functions are indistinguishable. A related approach, using a random walk formulation, allows us to identify the origin of correlations and self organization in the model, and to understand their disappearence for a different strategy's update rule, as pointed out in a previous work
Random global lies can enhance social efficiency: The story of Minority Game with a vivid memory  [PDF]
V. Sasidevan
Physics , 2015,
Abstract: The Minority Game (MG) is a prototypical model for an agent-based complex adaptive system. In MG, an odd number of heterogeneous and adaptive agents choose between two alternatives and those who end up on the minority side win. It is known that if $N$ agents play MG, they self-organize to a globally efficient state when they retain the memory of the minority side for the past $m \sim \log_2(N)$ rounds (Challet & Zhang 1997). However, the global efficiency becomes extremely low when the memory of the agents is reduced i.e, when $m << \log_2(N)$. In this work, we consider an MG in which agents use the information regarding the exact attendance on a side for $m$ previous rounds to predict the minority side in the next round. We show that, when employing such strategies, independent of its size, the system is always in a globally efficient state when the agents retain two rounds of information ($m=2$). Even with other values of $m$, the agents successfully self-organize to an efficient state, the only exception to this being when $m=1$ for large values of $N$. Surprisingly, in our model, providing the agents with a random $m=1$ fake history results in a better efficiency than real histories of any length.
Minority Game With Peer Pressure  [PDF]
H. F. Chau,F. K. Chow,K. H. Ho
Physics , 2003, DOI: 10.1016/j.physa.2003.10.009
Abstract: To study the interplay between global market choice and local peer pressure, we construct a minority-game-like econophysical model. In this so-called networked minority game model, every selfish player uses both the historical minority choice of the population and the historical choice of one's neighbors in an unbiased manner to make decision. Results of numerical simulation show that the level of cooperation in the networked minority game differs remarkably from the original minority game as well as the prediction of the crowd-anticrowd theory. We argue that the deviation from the crowd-anticrowd theory is due to the negligence of the effect of a four point correlation function in the effective Hamiltonian of the system.
The Minority Game: an introductory guide  [PDF]
Esteban Moro
Physics , 2004,
Abstract: The Minority Game is a simple model for the collective behavior of agents in an idealized situation where they have to compete through adaptation for a finite resource. This review summarizes the statistical mechanics community efforts to clear up and understand the behavior of this model. Our emphasis is on trying to derive the underlying effective equations which govern the dynamics of the original Minority Game, and on making an interpretation of the results from the point of view of the statistical mechanics of disordered systems.
Algorithmic Complexity in Minority Game  [PDF]
Ricardo Mansilla Corona
Physics , 1999,
Abstract: In this paper we introduce a new approach for the study of the complex behavior of Minority Game using the tools of algorithmic complexity, physical entropy and information theory. We show that physical complexity and mutual information function strongly depend on memory size of the agents and yields more information about the complex features of the stream of binary outcomes of the game than volatility itself.
The underlying complex network of the Minority Game  [PDF]
Ines Caridi,Horacio Ceva
Physics , 2008,
Abstract: We study the structure of the underlying network of connections in the Minority Game. There is not an explicit interaction among the agents, but they interact via global magnitudes of the model and mainly through their strategies. We define a link between two agents by quantifying the similarity among their strategies, and analyze the structure of the resulting underlying complex networks as a function of the number of agents in the game and the value of the agents' memory, in games with two strategies per player. We characterize the different phases of this system with networks with different properties, for this link definition. Thus, the Minority Game phase characterized by the presence of crowds can be identified with a small world network, while the phase with the same results as a random decision game as a random network. Finally, we use the Full Strategy Minority Game model, to explicitly calculate some properties of its networks, such as the degree distribution, for the same link definition, and to estimate, from them, the properties of the networks of the Minority Game, obtaining a very good agreement with its measured properties.
Intelligent Minority Game with genetic-crossover strategies  [PDF]
Marko Sysi-Aho,Anirban Chakraborti,Kimmo Kaski
Physics , 2002, DOI: 10.1140/epjb/e2003-00234-0
Abstract: We develop a game theoretical model of $N$ heterogeneous interacting agents called the intelligent minority game. The ``intelligent'' agents play the basic minority game and depending on their performances, generate new strategies using the one-point genetic crossover mechanism. The performances change dramatically and the game moves rapidly to an efficient state (fluctuations in the number of agents performing a particular action, characterized by $\sigma^2$, reaches a low value). There is no ``phase transition'' when we vary $\sigma^2/N$ with $2^M/N$, where $M$ is the ``memory''of an agent.
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