We present and analyse the behaviour of specialised operators designed for cooperative coevolution strategy in the framework of 3D tomographic PET reconstruction. The basis is a simple cooperative co-evolution scheme (the “fly algorithm”), which embeds the searched solution in the whole population, letting each individual be only a part of the solution. An individual, or fly, is a 3D point that...

a Radiometrics, 4909 Nautilus Court North, Boulder, CO, USA b National Center for Atmospheric Research, Boulder, CO, USA c Cooperative Institute for Research in the Environmental Sciences, Boulder, CO, USA d Center of Excellence for Severe Weather Forecast, L'Aquila, Italy e Institute of Methodologies for Environmental Analysis, Tito Scalo, Italy f Argonne National Laboratory, Argonne, IL, USA ...

In computer vision, co-segmentation is defined as the task of jointly segmenting the common objects in a given set of images. Most proposed cosegmentation algorithms have the assumptions that the common objects are singletons or with the similar size. In addition, they might assume that the background features are simple or discriminative. This paper presents a cooperative co-segmentation witho...

Co-evolution has been receiving increased attention as a method for multi agent simultaneous learning. This paper discusses how multiple robots can emerge cooperative behaviors through co-evolutionary processes. As an example task, a simpli ed soccer game with three learning robots is selected and a genetic programming method is applied to individual population corresponding to each robot so as...

given the importance of cooperatives in women's empowerment and the necessity of improving their performance, the present study was conducted to investigate factors or constructs discriminating successful and non-successful women's cooperatives to recognize the enabling conditions for cooperative's success. this was a co relational-survey type research in which 12819 of the membe...

When designing artificial neural network (ANN) it is important to optimise the network architecture and the learning coefficients of the training algorithm, as well as the time the network training phase takes, since this is the more timeconsuming phase. In this paper an approach to cooperative co-evolutionary optimisation of multilayer perceptrons (MLP) is presented. The cooperative co-evoluti...

This paper discusses how multiple robots can emerge cooperative and competitive behaviors through co-evolutionary processes. A genetic programming method is applied to individual population corresponding to each robot so as to obtain cooperative and competitive behaviors. The complexity of the problem can be explained twofold: coevolution for cooperative behaviors needs exact synchronization of...