Reinforcement Learning in Continuous Action Spaces | DDPG Tutorial (Tensorflow) скачать в хорошем качестве

Reinforcement Learning in Continuous Action Spaces | DDPG Tutorial (Tensorflow)

Let's use deep deterministic policy gradients to deal with the bipedal walker environment. Featuring a continuous action space and 24 elements in the observation vector, this is a perfect environment for a non trivial example of DDPG. #DDPG #BipedalWalker #DeepDeterministicPolicyGradients Learn how to turn deep reinforcement learning papers into code: Get instant access to all my courses, including the new Prioritized Experience Replay course, with my subscription service. $29 a month gives you instant access to 42 hours of instructional content plus access to future updates, added monthly. Discounts available for Udemy students (enrolled longer than 30 days). Just send an email to sales@neuralnet.ai https://www.neuralnet.ai/courses Or, pickup my Udemy courses here: Deep Q Learning: https://www.udemy.com/course/deep-q-l... Actor Critic Methods: https://www.udemy.com/course/actor-cr... Curiosity Driven Deep Reinforcement Learning https://www.udemy.com/course/curiosit... Natural Language Processing from First Principles: https://www.udemy.com/course/natural-... Reinforcement Learning Fundamentals https://www.manning.com/livevideo/rei... Here are some books / courses I recommend (affiliate links): Grokking Deep Learning in Motion: https://bit.ly/3fXHy8W Grokking Deep Learning: https://bit.ly/3yJ14gT Grokking Deep Reinforcement Learning: https://bit.ly/2VNAXql Come hang out on Discord here:   / discord   Need personalized tutoring? Help on a programming project? Shoot me an email! phil@neuralnet.ai Website: https://www.neuralnet.ai Github: https://github.com/philtabor Twitter:   / mlwithphil