Abstract. Validation can be used to detect when over tting starts during supervised training of a neural network; training is then stopped before convergence to avoid the over ttin...
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
In this paper, we use computational intelligence techniques to built quantitative models of player experience for a platform game. The models accurately predict certain key affecti...
Christopher Pedersen, Julian Togelius, Georgios N....
The main aim of this paper is to establish a reliable model both for the steady-state and unsteady-state regimes of a nonlinear process. The use of this model should reflect the t...