Reinforcement learning合集

this file contains:Advanced Deep Learning with Keras_ Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more (2018, Packt Publishing.pdf Deep Reinforcement Learning for Wireless Networks (2019, Springer International Publishing).pdf Deep Reinforcement Learning Hands-On_ Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more.pdf Hands-On Reinforcement Learning with Python_ Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow (2018, Packt Publishing).epub Hands-On Reinforcement Learning with Python_ Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow (2018, Packt Publishing).pdf Keras Reinforcement Learning Projects (2018, Packt Publishing).epub Keras Reinforcement Learning Projects (2018, Packt Publishing).pdf Practical Reinforcement Learning Develop self-evolving, intelligent agents with OpenAI Gym, Python and Java.pdf Python Reinforcement Learning Projects - 2018.pdf Reinforcement Learning for Optimal Feedback Control (2018, Springer International Publishing).pdf Reinforcement Learning with TensorFlow_ A beginner’s guide to designing self-learning systems with TensorFlow and OpenAI Gym (2018, Packt Publishing).pdf Reinforcement Learning _ With Open AI, TensorFlow and Keras Using Python-Apress (2018).pdf Reinforcement Learning_ An Introduction (2018, The MIT Press).pdf Simulation-Based Optimization_ Parametric Optimization Techniques and Reinforcement Learning (2015, Springer US).pdf Statistics for Machine Learning_ Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R-Packt Publishing (2017).pdf Tensorflow for Deep Learning_ From Linear Regression to Reinforcement Learning (2018, O'Reilly Media).pdf