In evolutionary computation, the fitness function normally measures progress toward an
objective in the search space, effectively acting as an objective function. Through deception …

Coevolutionary algorithms approach problems for which no function for evaluating potential
solutions is present or known. Instead, algorithms rely on the aggregation of outcomes from …

I present a new approach to evolutionary search called novelty search, wherein only
behavioral novelty is rewarded, thereby abstracting evolution as a search for novel forms …

Some major financial markets are currently reporting that 50% or more of all transactions are
now executed by automated trading systems (ATS). To understand the impact of ATS …

In a previous article, we introduced a number of visualization techniques that we had
developed for monitoring the dynamics of artificial competitive coevolutionary systems. One …

Abstract In April 2012, Rogers and Cliff (R&C) demonstrated a theoretical financial
brokerage model for cloud computing that is profitable for the broker, offers reduced costs for …

This research explores substitution of the fittest (SF), a technique designed to counteract the
problem of disengagement in two-population competitive coevolutionary genetic algorithms …

Given that evolutionary biologists have considered coevolutionary interactions since the
dawn of Darwinism, it is perhaps surprising that coevolution was largely overlooked during …

A novel approach for the autonomous virulence adaptation (AVA) of competing populations
in a coevolutionary optimization framework is presented. Previous work has demonstrated …

Coevolving systems are notoriously difficult to understand. This is largely due to the Red
Queen effect that dictates heterospecific fitness interdependence. In simulation studies of …