A series of evolutionary neural network simulations are presented which explore the hypothesis that learning factors can result in the evolution of long periods of parental protec...
Motivated by the growth of various networked systems as potential market places, we study market models wherein, owing to the size of the markets, transactions take place between l...
Atish Das Sarma, Deeparnab Chakrabarty, Sreenivas ...
Designing agents whose behavior challenges human players adequately is a key issue in computer games development. This work presents a novel technique, based on reinforcement lear...
Gustavo Andrade, Geber Ramalho, Hugo Santana, Vinc...
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
We present an application of a multi-agent cooperative search approach to the problem of optimizing gas pipeline operations, i.e. finding control parameters for a gas transmission...