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 paper studies an adaptive artificial agent model using a genetic algorithm to analyze how a population of decision-makers learns to coordinate on the selection of an equilibrium or a social convention in a two-sided matching game. In the contexts of centralized and decentralized entry-level...

The uncertainty of predicting stock prices emanates pre-eminent concerns around the functionality of the stock market. The possibility of utilising Genetic Algorithms to forecast the momentum of stock price has been previously explored by many optimisation models that have subsequently addressed...

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...

This paper proposes an algorithm to obtain maximum likelihood estimates of structural parameters in discrete games with multiple equilibria. The method combines a genetic algorithm (GA) with a pseudo maximum likelihood (PML) procedure. The GA searches efficiently over the huge space of possible...

Learning is modeled as an infection, which jumps from person to person. The rate of infection mimics individual discount rates and induces savings behavior on its own. It is shown that the apparent discount rate, the combination of the agents' true discount rate and the infection rate, decreases...

In this paper, I develop an algorithm for solving heterogeneous agent dynamic models in which individual decision rules influence each other. This approach is more general than the other heterogeneous agent solution methods in that it only requires a well formed objective function. The key...

Structural changes were the main focus of many studies in recent years. Changes which alter the socio-economic status of a nation from deprived and traditional nature to a developed and modern one. The main hypothesis of this study is that, the economic development does not occur through a...

This paper addresses the question of whether neural networks, a realistic cognitive model of the human information processing, can learn to backward induce in a two stage game with a unique subgame-perfect Nash Equilibrium. The result that the neural networks only learn a heuristic that...

In this paper we develop tests of functional form that are consistent against a class of nonlinear "smooth transition" models of the conditional mean. Our method is an extension of the consistent model specification tests developed by Bierens (1990), de Jong (1996) and Bierens and Ploberger...