Given the great amount of data that are generated of the experiments to analyze information of extracted chemical fluids of the brain of a rodent, arises the necessity to design an...
Abstract-- Understanding the evolvability of simple differentiating multicellular systems is a fundamental problem in the biology of genetic regulatory networks and in computationa...
Johannes F. Knabe, Chrystopher L. Nehaniv, Maria J...
— A technique for the visualization of stochastic population–based algorithms in multidimensional problems with known global minimizers is proposed. The technique employs proje...
Konstantinos E. Parsopoulos, Voula C. Georgopoulos...
This paper proposes an approach to the solution of multi-objective optimisation problems that delivers a single, preferred solution. A conventional, population-based, multiobjectiv...
Abstract-- In this paper we investigate the effects of individual learning on an evolving population of situated agents. We work with a novel type of system where agents can decide...
Abstract-- This paper presents an artificial homeostatic system (AHS) devoted to the autonomous navigation of mobile robots, with emphasis on neuro-endocrine interactions. The AHS ...
Abstract-- We investigate the usefulness of a subtree deactivation control mechanism which is open to evolutionary learning. It is hypothesised that this representation confers an ...
It is often suggested that traditional models of artificial evolution, based on explicit, human-defined fitness functions, are fundamentally more restricted and less creative than ...
In this paper, we present Creature Academy, a virtual laboratory that allows for the evolution of form and function within simulated physical 3D environments. Creature Academy can ...