This article describes the R package DEoptim which implements the differential evolution algorithm for the global optimization of a real-valued function of a real-valued parameter vector. The implementation of differential evolution in DEoptim interfaces with C code for efficiency. The utility...

This paper looks into the Greek – Turkish arms race a decade after an earlier contribution on the issue that relied heavily on Artificial Neural Networks. The time period between the two papers contributes to the reliability of the results derived, not just by increasing the number of...

In recent years, the government, of African Countries has assumed major responsibilities for economic reforms and growth. In attempting to describe their economies, economists (policymakers) in many African Countries have applied certain models that are by now widely known: Linear programming...

Introduction. The objects of investigation of this work are micro-level behaviors in stock markets. We aim at better understanding which strategies of market participants drive stock markets. The problem is that micro-level data from real stock markets are largely unobservable. We take an...

This paper aims at introducing a relative security measure, applicable to evaluating the impact of arms races on the military security of allies. This measure is based on demographic criteria, which play a dominant role in a number of arms races involving military alliances. The case of Greece...

Murphy, Koehler, and Fogler [1997] gave in the last issue of the Journal of Portfolio Management an account of how to raise a neural net’s IQ. The purpose of this reply is to point out some of the general difficulties with neural nets. Also, I would like to mention an alternative method,...

There has been an increased number of papers in the literature in recent years, applying several methods and techniques for exchange - rate prediction. This paper focuses on the Greek drachma using daily observations of the drachma rates against four major currencies, namely the U.S. Dollar...

This paper addresses the question of whether neural networks (NNs), a realistic cognitive model of human information processing, can learn to backward induce in a two-stage game with a unique subgame-perfect Nash equilibrium. The NNs were found to predict the Nash equilibrium approximately 70%...

This paper addresses how neural networks learn to play one-shot normal form games through experience in an environment of randomly generated game payoffs and randomly selected opponents. This agent based computational approach allows the modeling of learning all strategic types of normal form...