Reinforcement Learning

Reinforcement learning algorithms apply to problems in which it is necessary to optimize the path until reaching an objective, in an environment for which there is no exact modeling. Therefore, these methods use exploration and observation, learning based on the “reward” that the environment provides.

Deep Learning

Deep Learning, is one of the branches of Machine Learning using artificial neural networks for automated predictive processes

Machine Learning

Automatic learning or Machine Learning (ML) allow computers to learn by themselves from data. ML can extract patterns and models in a direct and more accurately way without human intervention.


Optimization, in broad strokes, is to select the best element with respect to some criteria, within the set of available elements. This application consists of maximizing or minimizing a function by choosing input values ​​of an allowed set and computing the value of the function.

Intelligent Observation Systems (IOS)

Intelligent Observation Systems (IOS) with Artificial Intelligence is used to extract expert´s knowledge and imitate human reasoning to automate process.


Helm is a constructive deterministic method (non-iterative), direct and completely reliable and which guarantees finding the correct operational solution. Signals the condition of voltage collapse when there is no solution

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