文件名称：Berkely Reinforcement Learning
文件大小：61.66MB
文件格式：RAR
更新时间：2022-03-16 07:38:29
增强学习 监督学习 迁移学习 多任务学习
伯克利大学的增强学习课件，youtube上有相应的视频教程
【文件预览】：
Berkely slides
----hw3-Q-learning and Actor-critic.pdf(184KB)
----lec-4-introduction to reinforcement learning.pdf(2.09MB)
----lec-2-supervised learning of behaviors.pdf(2.6MB)
----lec-13-Model-Based Rl and Policy Learning.pdf(2.52MB)
----lec-14-Variational Inference and Generative Models.pdf(2.13MB)
----lec-25-AutoMl.pdf(5.06MB)
----lec-1.pdf(3.55MB)
----hw2-Policy Gradients.pdf(187KB)
----lec-22-Advanced imitation learning and open problems.pdf(4.89MB)
----lec-11-Model-based Reinforcement learning.pdf(3.15MB)
----lec-20-Meta Reinforcement learning.pdf(9.14MB)
----lec-5-policy gradients.pdf(2.18MB)
----lec-24-Real-World Robot learning Safety and Flexibility.pdf(4.13MB)
----hw5b-Advanced Topics-Soft Actor-Critic.pdf(263KB)
----lec-16-Inverse Reinforcement learning.pdf(2.51MB)
----lec-10-optimal control and planning.pdf(2.36MB)
----hw1-Imitation learning.pdf(87KB)
----lec-9-Advanced policy gradients.pdf(1.38MB)
----lec-12-Advanced Model-Based Reinforcement Learning.pdf(2.91MB)
----lec-15-Reframing control as an Inference Problem.pdf(2.61MB)
----lec-8-Deep Rl with Q-function.pdf(2.19MB)
----lec-19-Transfer and Multi-Task learning.pdf(2.98MB)
----lec-17-Exploration(Part1).pdf(1.91MB)
----hw5a-Advanced Topics-Exploration.pdf(202KB)
----lec-3-Tensorflow Overview.pdf(277KB)
----hw4-Model-Based RL.pdf(192KB)
----lec-18-Exploration(Part2).pdf(2.46MB)
----lec-7-value function methods.pdf(1.66MB)
----lec-6-Actor Critic Algorithms.pdf(1.89MB)
----hw5c-Advanced Topics-Meta-learning Projects.pdf(208KB)
----lec-21-Distributed Rl.pdf(2.62MB)