Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
The goal of this project is to develop an agent capable of learning and behaving autonomously and making decisions quickly in a dynamic environment. The agent’s environment is a...
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
A possible alternative to fine topology tuning for Neural Network (NN) optimization is to use Echo State Networks (ESNs), recurrent NNs built upon a large reservoir of sparsely r...
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...