Proofs and empirical evidence are presented which show that a subset of algorithms can have identical performance over a subset of functions, even when the subset of functions is ...
Multiobjective methods are ideal for evolving a set of portfolio optimisation solutions that span a range from highreturn/high-risk to low-return/low-risk, and an investor can cho...
This paper introduces a procedure based on genetic programming to evolve XSLT programs (usually called stylesheets or logicsheets). XSLT is a general purpose, document-oriented fu...
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...
The hurdles in solving Constrained Optimization Problems (COP) arise from the challenge of searching a huge variable space in order to locate feasible points with acceptable solut...
Abu S. S. M. Barkat Ullah, Ruhul A. Sarker, David ...
This paper presents a new Genetic Algorithm for Protein Structure Prediction problem in both 2D and 3D hydrophobichydrophilic lattice models, introduced in [1]. Our algorithm evol...
This paper presents a theoretical definition for designing EDAs called Elitist Convergent Estimation of Distribution Algorithm (ECEDA), and a practical implementation: the Boltzm...
This paper merges hierarchical reinforcement learning (HRL) with ant colony optimization (ACO) to produce a HRL ACO algorithm capable of generating solutions for large domains. Th...
We propose an approach of automated co-evolution of the optimal values of attributes of active sensing (orientation, range and timing of activation of sensors) and the control of ...
This paper addresses the image registration problem applying genetic algorithms. The image registration’s objective is the definition of a mapping that best match two set of poi...