I am an optimist. It does not seem too much use being anything else. (2007)
Paul James Darwen, Paul James Darwen, Paul Darwen, Winston Spencer Churchill
by
1.1 Speciation in Co-evolutionary Learning (2007)
Abstract. Various extensions to the Genetic Algorithm (GA) attempt to find all or most optima in a search space containing several optima. Many of these emulate natural speciation. For...
A Convenient Method for the Synthesis of Cyclic Peptide Libraries (2005)
Bourne, Gregory T., Nielson, Jonathon L., Coughlan, Justin F., Darwen, Paul, Campitelli, Marc R., Horton, Douglas A., ...
A Convenient Method for the Synthesis of Cyclic Peptide Libraries (2005)
Bourne, Gregory T., Nielson, Jonathon L., Coughlan, Justin F., Darwen, Paul, Campitelli, Marc R., Horton, Douglas A., ...
A Convenient Method for Synthesis of Cyclic Peptide Libraries (2005)
Bourne, Gregory T., Nielson, Jonathon L., Coughlan, Justin F., Darwen, Paul, Campitelli, Marc Ronald, Horton, Douglas A., ...
Cyclic peptides have been reported to bind to multiple, unrelated classes of receptor with high affinity. Owing to the robustness of amide bond chemistry, the ability to explore extensive chemical...
A Convenient Method for Synthesis of Cyclic Peptide Libraries (2005)
Bourne, Gregory T., Nielson, Jonathon L., Coughlan, Justin F., Darwen, Paul, Campitelli, Marc Ronald, Horton, Douglas A., ...
Cyclic peptides have been reported to bind to multiple, unrelated classes of receptor with high affinity. Owing to the robustness of amide bond chemistry, the ability to explore extensive chemical...
There is a widespread perception that in conict situations, more intermediate choices between full peace and total war makes full peace less likely. This view is a motivation for opposing the...
Genetic Algorithms and Evolutionary Games (2000)
Genetic algorithms (GAs) have been used widely in evolving game-playing strategies since the mid-1980's. This paper looks at a particular game--- the iterated prisoner's dilemma game, which...
Marketing and Interdependent behaviour (2000)
This paper concentrates on the more complex and rich NIPD where N can be as large as 16. Three major issues will be investigated; (1) Can cooperation emerge from a population of random strategies? In...
Co-evolutionary learning by automatic modularisation with speciation (1996)
"6 November 1996" Includes bibliographical references (p. 213-227) and index
Co-evolutionary learning by automatic modularisation with speciation (1996)
"6 November 1996" Includes bibliographical references (p. 213-227) and index.
Exploiting population information in evolutionary learning (1996)
Xin Yao, Yong Liu, Paul Darwen
Evolutionary learning has been developing rapidly in the last decade. It is a powerful and general learning approach which has been used successfully in both symbolic systems, e.g., rule-based...
How to Make Best Use of Evolutionary Learning (1996)
Xin Yao, Yong Liu, Paul Darwen
Evolutionary learning has been developing rapidly in the last decade. It is a powerful and general learning approach which has been used successfully in both symbolic systems, e.g., rule-based...
Automatic Modularization by Speciation (1996)
Real-world problems are often too difficult to be solved by a single monolithic system. There are many examples of natural and artificial systems which show that a modular approach can reduce the...
Every Niching Method has its Niche: Fitness Sharing and Implicit Sharing Compared (1996)
Several extensions to the GA attempt to find all or most optima in a search space containing multiple optima. Many of these methods emulate speciation in natural evolution. Such methods must find all...
A dilemma for fitness sharing with a scaling function (1995)
Fitness sharing has been used widely in genetic algorithms for multi-objective function opti-mization and machine learning. It is often implemented with a scaling function, which adjusts an...
A dilemma for fitness sharing with a scaling function (1995)
Fitness sharing has been used widely in genetic algorithms for multi-objective function optimization and machine learning. It is often implemented with a scaling function, which adjusts an...
A Dilemma for Fitness Sharing with a Scaling Function (1995)
Fitness sharing has been used widely in genetic algorithms for multi-objective function optimization and machine learning. It is often implemented with a scaling function, which adjusts an...
How Good is Fitness Sharing with a Scaling Function (1995)
Fitness sharing has been used widely in genetic algorithms for multi-objective function optimization and machine learning. It is often implemented with a scaling function, which adjusts an...