reinforcement learning methods. Yury Chernyshov, UrFU, UDV Group

Data Ёлка 2020: Итоги года в Reinforcement Learning

DRL Course | Introduction to Reinforcement Learning. Cross-Entropy Method

DRL Course | Практическое занятие 1. Cross-Entropy Method

DRL Course | Практическое занятие 2. PyTorch and Deep Cross-Entropy Method.

DRL Course | Dynamic Programming. Policy and Value Iterations

DRL Course | Model-Free Reinforcement Learning: Monte-Carlo, SARSA, Q-Learning

DRL Course | Introduction to Neural Networks. Deep Cross-Entropy Method

DRL Course | Практическое занятие 4. Monte-Carlo and SARSA

DRL Course | Value Function Approximation. Deep Q-Networks (DQN)

DRL Course | Практическое занятие 3. Policy Iteration

DRL Course | Практическое занятие 6. Deep Deterministic Policy Gradient (DDPG)

DRL Course | Разбор домашних заданий 1-3

DRL Course | Практическое занятие 5. Deep Q-Networks (DQN)

DRL Course | Policy Gradient

DRL Course | Разбор домашних заданий 4-6. Подведение итогов курса

DRL Course 2023 | Introduction to Reinforcement Learning. Cross-Entropy Method

DRL Course 2023 | Introduction to Neural Networks. Deep Cross-Entropy Method

DRL Course 2023 | Практическое занятие 1. Cross-Entropy Method.

DRL Course 2023 | Model-Free Reinforcement Learning: Monte-Carlo, SARSA, Q-Learning

DRL Course 2023 | Практическое занятие 2. PyTorch and Deep Cross-Entropy Method.

DRL Course 2023 |Dynamic Programming. Policy and Value Iterations