In the early days a policy was a set of simple rules with a clear intuitive motivation that could be formalised to good effect. However the world is becoming much more complex. S...
Yow Tzu Lim, Pau-Chen Cheng, Pankaj Rohatgi, John ...
In this paper we investigated the use of Genetic Programming (GP) to evolve programs which could detect moving objects in videos. Two main approaches under the paradigm were propo...
We describe the application of genetic programming (GP) to a problem in pure mathematics, in the study of finite algebras. We document the production of human-competitive results...
Lee Spector, David M. Clark, Ian Lindsay, Bradford...
We investigated how indexed FOR-loops, such as the ones found in procedural programming languages, can be implemented in genetic programming. We use them to train programs that le...
The study of common, complex multifactorial diseases in genetic epidemiology is complicated by nonlinearity in the genotype-to-phenotype mapping relationship that is due, in part,...
Ryan J. Urbanowicz, Nate Barney, Bill C. White, Ja...
This paper examines the impact of semantic control on the ability of Genetic Programming (GP) to generalise via a semantic based crossover operator (Semantic Similarity based Cross...
Nguyen Quang Uy, Nguyen Thi Hien, Nguyen Xuan Hoai...
Nested Monte-Carlo search is a general algorithm that gives good results in single player games. Genetic Programming evaluates and combines trees to discover expressions that maxim...
Genetic programming approaches have previously been employed in the literature to evolve heuristics for various combinatorial optimisation problems. This paper presents a hyper-heu...
We propose an evolutionary method for detection of vehicles in satellite imagery which involves a large number of simple elementary features and multiple detectors trained by genet...
Krzysztof Krawiec, Bartosz Kukawka, Tomasz Macieje...
This paper describes the recently developed genetic programming paradigm which genetically breeds populations of computer programs to solve problems. In genetic programming, the i...