Reinforcement learning training method and decision-making method based on reinforcement learning

Abstract

The invention provides a reinforcement learning training method and a decision-making method based on reinforcement learning, and the method comprises the following steps: obtaining a plurality of groups of historical state data; inputting each group of historical state data into a reinforcement learning model to obtain preliminary decision data; inputting each group of historical state data and the preliminary decision data into a pre-established Bayesian neural network model to obtain a state variable quantity and a reward value, the state variable quantity being a difference value between current state data and next state data; and updating model parameters of the reinforcement learning model according to each group of historical state data, the corresponding preliminary decision data,the state variation and the reward value. By implementing the method, the training sample size of the reinforcement learning model can be increased, the reinforcement learning effect is improved, andthe accuracy of a dynamic decision planning result is improved.

Description

Technical field [0001] The present invention relates to the field of machine learning, and more particularly to an intensive learning training method and a decision-making method based on strengthening learning. Background technique [0002] At present, strengthen learning is an effective way to dynamically decision planning for multiple application scenarios. It pays attention to how the subject should act in an environment to achieve maximum cumulative reward. Strengthen learning and application scenarios generally include traffic, finance, energy, commercial management and other fields, such as the use of strengthening learning to flight cabin by using multiple state data based on flights (such as number of remaining cabin sales, class sales). Perform control management. [0003] In the relevant technique, when the model is enhanced, a large amount of status data is required to facilitate training that the reinforced learning model is trained. In fact, the true state data gene...

AI Technical Summary

Problems solved by technology

[0004] In view of this, the embodiment of the present invention provides a reinforcement learning training method and a reinforcement learning-based decision-making method to solve the defect of inaccurate dynamic decision planning results in the prior art

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