This paper rectifies a design problem in the Santa Fe Artificial Stock Market Model. Due to a faulty mutation operator, the resulting bit distribution in the classifier system was systematically upwardly biased, thus suggesting increased levels of technical trading for smaller GA-invocation...

Multi-Agent Based Simulation is a branch of Distributed Artificial Intelligence that builds the base for computer simulations which connect the micro and macro level of social and economic scenarios. This paper presents a new method of modelling the formation and change of patterns of action in...

This study presents an experimental approach to strategic behavior and economic learning by integrating game theory and Genetic Algorithms in a novel heuristic-based simulation model. Inspired by strategic scenarios that change over time, we propose a model where games can change based on...

This study presents an experimental approach to strategic behavior and economic learning by integrating game theory and Genetic Algorithms in a novel heuristic-based simulation model. Inspired by strategic scenarios that change over time, we propose a model where games can change based on...

In experimental data, it is common to find persistent oscillations in the aggregate outcomes and high levels of heterogeneity in individual behavior. Furthermore, it is not unusual to find significant deviations from aggregate Nash equilibrium predictions. In this paper, we employ an...

The conditioning of strategies by market environment and the simultaneous emergence of market structure in the presence of evolving trading strategies are investigated with major international stock indexes. Models for price forecasting and trading strategies evolution are examined under...

Using virtual stock markets with artificial interacting software investors, aka agent-based models, we present a method to reverse engineer real-world financial time series. We model financial markets as made of a large number of interacting boundedly rational agents. By optimizing the...

The classical game theoretic resolutions to Selten’s Chain Store game are unsatisfactory; they either alter the game to avoid the paradox or struggle to organize the existing experimental data. This paper applies co-evolutionary algorithms to the Chain Store game and demonstrates that the...