Parent Selection Pressure Auto-Tuning for Tournament Selection in Genetic Programming
Selection pressure restrains the selection of individuals from the current population to produce a new population in the next generation. It gives individuals of higher quality a higher probability of being used to create the next generation so that ...
A Hybrid Multiobjective Evolutionary Algorithm for Multiobjective Optimization Problems
Recently, the hybridization between evolutionary algorithms and other metaheuristics has shown very good performances in many kinds of multiobjective optimization problems (MOPs), and thus has attracted considerable attentions from both academic and ...
Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers
Evolvable hardware (EHW) has shown itself to be a promising approach for prosthetic hand controllers. Besides competitive classification performance, EHW classifiers offer self-adaptation, fast training, and a compact implementation. However, EHW ...
A New Sequential Covering Strategy for Inducing Classification Rules With Ant Colony Algorithms
Ant colony optimization (ACO) algorithms have been successfully applied to discover a list of classification rules. In general, these algorithms follow a sequential covering strategy, where a single rule is discovered at each iteration of the algorithm ...
Objective Reduction in Many-Objective Optimization: Linear and Nonlinear Algorithms
The difficulties faced by existing multiobjective evolutionary algorithms (MOEAs) in handling many-objective problems relate to the inefficiency of selection operators, high computational cost, and difficulty in visualization of objective space. While ...
On the Advantages of Variable Length GRNs for the Evolution of Multicellular Developmental Systems
Biological genomes have evolved over a period of millions of years and comprise thousands of genes, even for the simplest organisms. However, in nature, only 1–2% of the genes play an active role in creating and maintaining the organism, while the ...
The Transferability Approach: Crossing the Reality Gap in Evolutionary Robotics
The reality gap, which often makes controllers evolved in simulation inefficient once transferred onto the physical robot, remains a critical issue in evolutionary robotics (ER). We hypothesize that this gap highlights a conflict between the efficiency ...
The Use of an Analytic Quotient Operator in Genetic Programming
We propose replacing the division operator used in genetic programming with an analytic quotient (AQ) operator. We demonstrate that this AQ operator systematically yields lower mean squared errors over a range of regression tasks, due principally to ...