Now showing items 1-3 of 3
A novel artificial hydrocarbon networks based value function approximation in hierarchical reinforcement learning
(Springer Verlag, 2017)
Reinforcement learning aims to solve the problem of learning optimal or near-optimal decision-making policies for a given domain problem. However, it is known that increasing the dimensionality of the input space (i.e. ...
Stochastic parallel extreme artificial hydrocarbon networks : an implementation for fast and robust supervised machine learning in high-dimensional data
(Elsevier Ltd., 2020-03)
Artificial hydrocarbon networks (AHN) – a supervised learning method inspired on organic chemical structures and mechanisms – have shown improvements in predictive power and interpretability in comparison with other ...
Versatility of artificial hydrocarbon networks for supervised learning
(Springer Verlag, 2019)
Surveys on supervised machine show that each technique has strengths and weaknesses that make each of them more suitable for a particular domain or learning task. No technique is capable to tackle every supervised learning ...