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  1. Population optimization algorithms: Resistance to getting stuck in local extrema (Part I)

    by , 09-29-2024 at 06:39 AM
    This is a unique research, the idea for which came to me while answering questions that arose during the discussion of one of my articles. I am hopeful that readers will appreciate the value and originality of this work.

    To carry out the experiment, we need to first initialize the coordinates of the agents forcibly outside the algorithm, using the coordinates of the global minimum, before measuring the fitness function at the first epoch.

    Such an experiment will
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  2. Data Science and Machine Learning (Part 19): Supercharge Your AI models with AdaBoost

    by , 09-28-2024 at 08:07 AM
    Adaboost, short for adaptive boosting is an ensemble machine learning model that attempts to build a strong classifier out of weak classifiers.
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  3. New Photos Reveal Holes in NASA Mars Rover Wheels, but They're Still Turning

    by , 09-28-2024 at 05:57 AM
    NASA's Curiosity rover has been exploring the Gale Crater on Mars since 2012. That's a long time to weather dust storms, drive along the base of a mountain and crawl over endless pointy rocks. The rover's aluminum wheels have taken a beating. New images show some dramatic gaping holes, but don't be alarmed. NASA has it under control.
    The photos are eye-opening. Curiosity has six wheels and some are worse off than others. The right-middle wheel looks rough, but "is still holding up well despite ...
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  4. MQL5 Wizard Techniques you should know (Part 35): Support Vector Regression

    by , 09-26-2024 at 12:32 PM
    Support Vector Regression (SVR) is a form of regression derived from Support Vector Machines. At its core, SVR uses kernel methods to map input data into higher-dimensional spaces, allowing for more complex relationships to be captured, which contrasts with dimensionality reduction. For this article though we are exploring strictly its loss function role when used with a multi-layer perceptron. A related but different form of regression we looked at in an earlier article was Gaussian Process
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  5. MQL5 Wizard Techniques you should know (Part 36): Q-Learning with Markov Chains

    by , 09-26-2024 at 09:36 AM
    Custom signal classes for wizard assembled Expert Advisors can take on various roles, that are worth exploring, and we continue this quest by examining how the Q-Learning algorithm when paired with Markov Chains can help refine the learning process of a multi-layer-perceptron network. Q-Learning is one of the several (approximately 12) algorithms of reinforcement-learning, so essentially this is also a look at how this subject can be implemented as a custom signal and tested within a wizard
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