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Found 4 papers, 3 papers with code
Room Clearance with Feudal Hierarchical Reinforcement Learning
Reinforcement learning (RL) is a general framework that allows systems to learn autonomously through trial-and-error interaction with their environment.
Hierarchical Reinforcement Learning
reinforcement-learning
+1
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning
Training agents to autonomously learn how to use anthropomorphic robotic hands has the potential to lead to systems capable of performing a multitude of complex manipulation tasks in unstructured and uncertain environments.
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals
Learning with sparse rewards remains a significant challenge in reinforcement learning (RL), especially when the aim is to train a policy capable of achieving multiple different goals.
Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect Information
We introduce a new virtual environment for simulating a card game known as "Big 2".
