filmov
tv
Reinforcement Learning with sparse rewards
Показать описание
In this video I dive into three advanced papers that addres the problem of the sparse reward setting in Deep Reinforcement Learning and pose interesting research directions for mastering unsupervised learning in autonomous agents.
Papers discussed:
Reinforcement Learning with Unsupervised Auxiliary Tasks - DeepMind:
Curiosity Driven Exploration - UC Berkeley:
Hindsight Experience Replay - OpenAI:
If you want to support this channel, here is my patreon link:
Papers discussed:
Reinforcement Learning with Unsupervised Auxiliary Tasks - DeepMind:
Curiosity Driven Exploration - UC Berkeley:
Hindsight Experience Replay - OpenAI:
If you want to support this channel, here is my patreon link:
Reinforcement Learning with sparse rewards
Reward Shaping
Handling Sparse Rewards in Reinforcement Learning Using Model Predictive Control
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
[Presentation] Action Guidance: Getting the Best of Sparse Rewards and Shaped Rewards for RTS Games
Task Specification for Reinforcement Learning on Real Robots Using Sparse Rewards
Overcome Sparse Rewards in Reinforcement Learning
Understanding Reinforcement Learning Environment and Rewards
Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning
Learning to Generalise in Sparse Reward Navigation Environments
Design the Best Reward Function | Reinforcement Learning Part-6
Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards
Upside-Down Reinforcement Learning
An introduction to Reinforcement Learning
Nearly Minimax Optimal Reward-Free Reinforcement Learning
Reinforcement Learning with TensorFlow and Unity - Pittsburgh ML Summit ‘19
Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions
Reinforcement Learning: Machine Learning Meets Control Theory
Navigating Sparse Rewards in RL
AI Seminar Series 2024: Exploring in Sparse-Reward Domains, Dr. Guni Sharon
Training AI Without Writing A Reward Function, with Reward Modelling
Cooperative Navigation - Sparse Reward Function
MIT 6.S094: Deep Reinforcement Learning
Go-Explore: a New Approach for Hard-Exploration Problems
Комментарии