The Santa Fe Artificial Stock Market [13, 4] is an agent-based artificial model in which agents continually explore and develop expectational models, buy and sell assets based on the predictions of those models that perform best, and confirm or discard these models based on their performance...

In this paper we study a simple learning paradigm for iterated normal form games in an evolutionary context. Following the decision theoretic concept of satisficing we design players with a certain aspiration level. If their payoff is below this level, they change their current action, otherwise...

Communication plays a vital role in the organization and operation of biological, computational, economic, and social systems. Agents often base their behavior on the signals they receive from others and also recognize the importance of the signals they send. Here we develop a framework for...

The evolution of cooperation in the repeated prisoner's dilemma depends on the conditions under which the game is played. The results of a series of computer simulations show that the emergence of cooperative play in the game is strongly affected by the localisations of both interaction and...

The paper describes the application of Genetic Algorithms to a Resource Economics problem; the decision about the intensity of exploitation of a renewable resource. Genetic Algorithms, developed by HOLLAND (1975), are a model of biological evolution, that captures some important features of...

In this paper we introduce a new approach to optimization problems based on a previous theoretical work on extinction patterns in macroevolution. We name them Macroevolutionary Algorithms (MA). Unlike population-level evolution, which is employed in standard genetic algorithms, evolution at the...

Environmental and biotic factors regulate species abundance and the composition of ecological communities. However, it is difficult to demonstrate principles of community assembly in nature due to observational limitations and historical effects. Numerical simulation can be used to evaluate...

Fitness distance correlation (FDC) has been offered as a summary statistic with apparent success in predicting the performance of genetic algorithms for global optimization. Here, a counterexample to Hamming-distance based FDC is examined for what it reveals about how GAs work. The...

Current techniques of DNA analysis enable the scoring of hundreds of electrophoretic bands using a small amount of DNA from an individual. The sample size in pilot experiments is typically orders of magnitude smaller then the number of bands contained in a molecular profile. Nevertheless, it is...

Previous work on coevolutionary search has demonstrated both successful and unsuccessful applications. As a step in explaining what factors lead to success or failure, we present a comparative study of an evolutionary and a coevolutionary search model. In the latter model, strategies for solving...