Abstract. Spector et al. have shown [1],[2],[3] that genetic programming can be used to evolve quantum circuits. In this paper, we present new results in this field, introducing p...
Abstract. We use case injected genetic algorithms to learn to competently play computer strategy games. Such games are characterized by player decision in anticipation of opponent ...
Abstract. The paper focuses on the efficiency of the hybrid evolutionary algorithm (HEA) for solving the global optimization problem arising in electronic imaging. The particular v...
Multiplicative general parameter (MGP) approach to finite impulse response (FIR) filtering introduces a novel way to realize cost effective adaptive filters in compact very large s...
This paper presents an improved version of a simple evolution strategy (SES) to solve global nonlinear optimization problems. As its previous version, the approach does not require...
Abstract. We introduce a framework for brain modelling tasks, following a collaborative coevolutionary approach. A new coevolutionary scheme is also proposed which emphasizes colla...
We illustrate with two simple examples how Interactive Evolutionary Computation (IEC) can be applied to Exploratory Data Analysis (EDA). IEC is particularly valuable in an EDA cont...
Abstract. In this work we have implemented and analyzed the performance of a new real coded steady-state genetic algorithm (SSGA) for the flexible ligand-receptor docking problem....
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Abstract. Bloat is a common and well studied problem in genetic programming. Size and depth limits are often used to combat bloat, but to date there has been little detailed explor...
Nicholas Freitag McPhee, Alex Jarvis, Ellery Fusse...