深度强化学习必读文献

【文件属性】：
文件名称：深度强化学习必读文献
文件大小：32.81MB
文件格式：ZIP
更新时间：2022-03-14 09:04:49
人工智能 深度强化学习 深度强化学习的入门经典文献： 包括DQN、DDPG、A3C/A2C/PPO/ACKTR等； 包括模仿学习，也包括几篇综述性的文章。

【文件预览】：
DRL文献
----PARAMETER SPACE NOISE FOR EXPLORATION.pdf(3.78MB)
----Natural Actor-Critic.pdf(783KB)
----Generative Adversarial Imitation Learning.pdf(501KB)
----Maximum Entropy Inverse Reinforcement Learning.pdf(391KB)
----Large Scale Distributed Deep Networks.pdf(309KB)
----A Connection Between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models.pdf(108KB)
----NOISY NETWORKS FOR EXPLORATION.pdf(5.29MB)
----Natural actor–critic algorithms.pdf(2.49MB)
----Composable Deep Reinforcement Learning for Robotic Manipulation.pdf(2.91MB)
----Distributed Prioritized Experience Replay.pdf(2.86MB)
----SOFT ACTOR-CRITIC_ OFF-POLICY MAXIMUM ENTROPY DEEP REINFORCEMENT LEARNING WITH A STOCHASTIC ACTOR.pdf(2.69MB)
----Asynchronous Methods for Deep Reinforcement Learning.pdf(2.2MB)
----Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation.pdf(4.91MB)
----Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates.pdf(2.28MB)
----Reinforcement Learning with Deep Energy-Based Policies.pdf(3.47MB)
----Massively Parallel Methods for Deep Reinforcement Learning.pdf(2.71MB)
----Deep Q-learning from Demonstrations.pdf(426KB)