We present empirical evidence that long-term evolutionary dynamics fall into three distinct classes, depending on whether adaptive evolutionary activity is absent (class 1), bounded (class 2), or unbounded (class 3). These classes are defined using three statistics: diversity, new evolutionary...

We use game theory and the Santa Fe Artificial Stock Market, an agent-based model of an evolving stock market, to study the properties of strategic Nash equilibria in financial markets. We discover two things: there is a unique strategic equilibrium in the market, and this equilibrium in...

The widespread use and proven profitability of technical trading rules in financial markets has long been a puzzle in academic finance. In this paper we show, using an agent-based model of an evolving stock market, that widespread technical trading can arise due to a multi-person prisoners'...

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...

We introduce a method for visualizing evolutionary activity of genotypes. Following a proposal of Bedau and Packard[11], we define a genotype's evolutionary activity in terms of the history of its concentration in the evolving population. To visualize this evolutionary activity we graph the...

Bedau and Packard [7] devised an approach to quantifying the adaptive phenomena in artificial systems. We use this approach to define two statistics: cumulative evolutionary activity and mean cumulative evolutionary activity. Then we measure the dynamics of cumulative evolutionary activity, mean...