Now showing items 1-5 of 5
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. ...
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 ...
Human activity recognition on mobile devices using artificial hydrocarbon networks
(Springer Verlag, 2018)
Human activity recognition (HAR) aims to classify and identify activities based on data-driven from different devices, such as sensors or cameras. Particularly, mobile devices have been used for this recognition task. ...
A comparative analysis of evolutionary learning in artificial hydrocarbon networks
(Springer Science and Business Media Deutschland GmbH, 2020-10-07)
Artificial hydrocarbon networks (AHN) is a supervised learning model that is loosely inspired on the interactions of molecules in organic compounds. This method is able to model data in a hierarchical and robust way. ...
Towards artificial hydrocarbon networks : The chemical nature of data-driven approaches
(Institute of Electrical and Electronics Engineers Inc., 2019-04-08)
Inspiration in nature has been widely explored, from macro to micro-scale. Natural phenomena mainly considers adaptability, optimization, robustness, organization, among other properties, to deal with complexity. When ...