The issue of efficient exploration of the environment is one of the main problems of reinforcement learning methods. We have discussed this issue more than once. Each time, a proposed solution led to additional complication of the algorithm. In most cases, we resorted to using additional internal reward mechanisms to encourage the model to explore new actions and search for unexplored paths. more...
Regression is a task of predicting a real value from an unlabeled example. A well-known example of regression is estimating the value of a diamond based on such characteristics as size, weight, color, clarity, etc. The so-called regression metrics are used to assess the accuracy of regression model predictions. Despite similar algorithms, regression metrics are semantically different from similar loss functions. more...
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