Intro to Transition Probabilities and OpenAI Gym Library – Reinforcement Learning Tutorial
#machinelearning #reinforcementlearning #reinforcement #machinelearningtutorial #machinelearningengineer #datascience #datasciencecareer #datasciencetutorial #controlengineering #controltheory #controltheory #controlsystems #dynamicprogramming #dynamicalsystems
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https://aleksandarhaber.com/introduction-to-state-transition-probabilities-actions-and-rewards-with-openai-gym-reinforcement-learning-tutorial/
In this video tutorial, we introduce important concepts for understanding reinforcement learning algorithms. These concepts are transition probabilities, transition states, terminal states, episodes, and rewards. We use the OpenAI Gym Python library to illustrate these concepts. More precisely, we use the Frozen Lake environment.
#machinelearning #reinforcementlearning #reinforcement #machinelearningtutorial #machinelearningengineer #datascience #datasciencecareer #datasciencetutorial #controlengineering #controltheory #controltheory #controlsystems #dynamicprogramming #dynamicalsystems
It takes a significant amount of time and energy to create these free video tutorials. You can support my efforts in this way:
– Buy me a Coffee: https://www.buymeacoffee.com/AleksandarHaber
– PayPal: https://www.paypal.me/AleksandarHaber
– Patreon: https://www.patreon.com/user?u=32080176&fan_landing=true
– You Can also press the Thanks YouTube Dollar button
The post accompanying this video is given here:
Introduction to State Transition Probabilities, Actions, Episodes, and Rewards with OpenAI Gym Python Library- Reinforcement Learning Tutorial
In this video tutorial, we introduce important concepts for understanding reinforcement learning algorithms. These concepts are transition probabilities, transition states, terminal states, episodes, and rewards. We use the OpenAI Gym Python library to illustrate these concepts. More precisely, we use the Frozen Lake environment.
