We use a parallel multi-objective genetic algorithm to drive a search and reconstruction spectroscopic analysis of plasma gradients in inertial confinement fusion (ICF) implosion...
The tagging problem in natural language processing is to find a way to label every word in a text as a particular part of speech, e.g., proper noun. An effective way of solving th...
We investigate the results of coevolution of spatially distributed populations. In particular, we describe work in which a simple function approximation problem is used to compare...
Mapping biology into computation has both a domain specific aspect – biological theory – and a methodological aspect – model development. Computational modelers have implici...
Janet Wiles, Nicholas Geard, James Watson, Kai Wil...
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
The problem attempted in this paper is to select a sample from a large set where the sample is required to have a particular average property. The problem can be expressed as an o...
As the paradigm of object orientation becomes more and more important for modern IT development projects, the demand for an automated test case generation to dynamically test obje...
In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from ...
Embedded Cartesian Genetic Programming (ECGP) is a form of the graph based Cartesian Genetic Programming (CGP) in which modules are automatically acquired and evolved. In this pap...