Colin Fyfe


Colin Fyfe is an active researcher in Artificial Neural Networks, Genetic Algorithms, Artificial Immune Systems and Artificial Life having written over 250 refereed papers, several book chapters and two books. He is a member of the Editorial Board of the International Journal of Knowledge-Based Intelligent Engineering Systems and an Associate Editor of International Journal of Neural Systems. He currently supervises 6 PhD students and has been Director of Studies for 16 PhDs since 1998. He is a member of the Academic Advisory Board of the International Computer Science Conventions group and a Committee member of the European Network of Excellence on Intelligent Technologies for Smart Adaptive Systems (EUNITE). He has been Visiting Researcher at the University of Strathclyde, the Riken Institute in Tokyo, the Chinese University of Hong Kong, and Visiting Professor at the University of Vigo, the University of Burgos, and the University of Salamanca, all in Spain.

Publications

Biologically Inspired Artificial Intelligence for Computer Games
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 278 pages.
Computer games are often played by a human player against an artificial intelligence software entity. In order to truly respond in a human-like manner, the...
Contemporary Video Game AI
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 11 pages.
This chapter provides a brief outline of the history of video game AI – and hence by extension an extremely brief outline of some of the key points in the history...
An Introduction to Artificial Neural Networks
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 12 pages.
The design of the first computers were influenced by the power of the human brain and attempts to create artificial intelligence, yet modern day digital computers...
Supervised Learning with Artificial Neural Networks
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 17 pages.
In this chapter we will look at supervised learning in more detail, beginning with one of the simplest (and earliest) supervised neural learning algorithms – the...
Case Study: Supervised Neural Networks in Digital Games
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 7 pages.
In this short chapter we present a case study of the use of ANN in a video game type situation. The example is one of duelling robots, a problem which, as we will...
Unsupervised Learning in Artificial Neural Networks
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 43 pages.
With the artificial neural networks which we have met so far, we must have a training set on which we already have the answers to the questions which we are going...
Fast Learning in Neural Networks
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 14 pages.
We noted in the previous chapters that, while the multilayer perceptron is capable of approximating any continuous function, it can suffer from excessively long...
Genetic Algorithms
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 16 pages.
The methods in this chapter were developed in response to the need for general purpose methods for solving complex optimisation problems. A classical problem...
Beyond the GA: Extensions and Alternatives
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 18 pages.
The last two chapters introduced the standard GA, presented an example case study and explored some of the potential pitfalls in using evolutionary methods. This...
Evolving Solutions for Multiobjective Problems and Hierarchical AI
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 11 pages.
Multi-Objective Problems, MOP, are a class of problems for which different, competing, objectives are to be satisfied and for which there is generally no single...
Artificial Immune Systems
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 30 pages.
We now consider the problem of introducing more intelligence into the artificial intelligence’s responses in real-time strategy games (RTS). We discuss how the...
Ant Colony Optimisation
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 22 pages.
Ants are truly amazing creatures. Most species of ant are virtually blind; some of which have no vision at all, yet despite this, they are able to explore and find...
Reinforcement Learning
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 25 pages.
Just as there are many different types of supervised and unsupervised learning, so there are many different types of reinforcement learning. Reinforcement learning...
Adaptivity within Games
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 12 pages.
This book centres on biologically inspired machine learning algorithms for use in computer and video game technology. One of the important reasons for employing...
Turing's Test and Believable AI
Darryl Charles, Colin Fyfe, Daniel Livingstone, Stephen McGlinchey. © 2008. 17 pages.
It is very evident that current progress in developing realistic and believable game AI lags behind that in developing realistic graphical and physical models. For...
Visualizing Multi Dimensional Data
César García-Osorio, Colin Fyfe. © 2008. 41 pages.
This chapter gives a survey of some existing methods for visualizing multi dimensional data, that is, data with more than 3 dimensions. To keep the size of the...
Computational Intelligence and its Applications
Lakhmi Jain, Colin Fyfe, Ngoc Thanh Nguyen.
The Computational Intelligence and its Applications (COMIA) Book Series encompasses all branches of artificial intelligence which are based on computation at some...