Self-Organized Segregation within an Evolving Population

Abstract

An evolving population, in which individual members ('agents') adapt their behaviour according to past experience, is of central importance to many disciplines. Because of their limited knowledge and capabilities, agents are forced to make decisions based on inductive, rather than deductive, thinking.We show that a population of competing agents with similar capabilities and knowledge will tend to self-segregate into opposing groups characterized by extreme behavior. Cautious agents perform poorly and tend to become rare.

Dynamical spin-glass-like behavior in an evolutionary game

“…It was found, that the properties of the game depend on the memory length M and number of players N through the scaling variable α = 2 M /N [4,6,7]. The Minoriry game was thoroughly studied both numerically and analytically [8][9][10][11][12][13][14][15][16][17][18][19] along with the study of the original bar attendance problem [20,21] and various modifications of the Minority game [22][23][24][25][26][27][28][29] An important role is attributed to the observation that the dynamics of the memorized pattern and the strategies' scores are in certain regimes decoupled [30][31][32] and that the thermal noise can ge introduced in the players' decisions [33][34][35].…”

Crowd–anticrowd theory of the minority game

“…In modified MG models such as Ref. [11] which features evolving stochastic strategies, this frustration is able to relax -similar sized crowds and anti-crowds hence emerge yielding a smaller-than-random σ for general m.…”

Capital flow in a two-component dynamical system

“…More abstract approach is used in the minority game model [18][19][20][21][22][23][24][25][26][27][28][29], where real money is lacking. An important feature of this model is the presence of a transition from chaotic to periodic phase, when the number of players is increased.…”

“…Like in these problems, numerical simulations of various "minimal" models of economic behavior [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29] play important role, in parallel with analytical approaches [29][30][31][32][33][34][35][36]. Even though the hope of detailed prediction of the future market behavior could be (at least very probably) rarely satisfied, the knowledge of parameters, which are crucial for the probabilistic properties of the economic events is very important to the decision-makers on all levels.…”