CSCS I-SPOC

Many papers focused on fine-tunning the Gene Expression Programming (GEP) operators or their application rates in order to improve the performances of the algorithm. Much less work was done on optimizing the structural parameters of the chromosomes (i.e. number of genes and gene size). This is probably due to the fact that the No Free Lunch theorem states that no fixed values for these parameters will ever suit all problems. To counteract this fact, this paper presents a modified GEP algorithm, called AdaGEP, which automatically adapts the number of genes used by the chromosome.

This paper presents a method for searching ground states of Ising spin glasses. The Ising model is one of the most commonly used because of its simplicity and its accuracy in representing real problems. We tackle the problem of finding ground states with particle swarm optimization (PSO), a population-based stochastic optimization technique inspired by social behavior of bird flocking.

It is known that Fredholm integral equations of the first kind occur when solving with problems of synthesis of electrostatic and magnetic fields. This paper presents two approaches for solving such an equation. The first one involves discretization by a collocation method and numerical solution using an approximate orthogonalization algorithm. The second method is based on a nature inspired heuristic, namely genetic programming.

Analysis of Lotka Voltera population equations indicates that complex food webs should be unstable and predicts the presence of fewer species than are observed in real food-webs. The question of diversity verses stability has been partially resolved by including spatial and temporal heterogeneity. This model simultaneously compares an ABM of multi-species agents with a simple equation-based model. A heterogeneous “landscape” can change the interactions between agents, and a refugia provides an area where the predator species is excluded.

Cognitive redeployment is the idea that an important part of the evolution of cognition is the adaptation and re-use of existing cognitive modules for new purposes. Here, components of the ACT-R cognitive architecture are repurposed to develop novel models. In particular, the decelarative memory system is used to create a new vision system, and the salience system from ACT-R vision is integrated with declarative memory to produce a novel explanation for the release from proactive interference effect.