Simple Implementations of RL Algorithm in PyTorch
-
Updated
Nov 16, 2021 - Python
Simple Implementations of RL Algorithm in PyTorch
Testing different Reinforcement Learning strategies inspired by hippocampal replay for robotic navigation
Example FRWR (PDDM) implementation with ReLAx
A repostiory to generate grid activation for an environment
Control of InvertedPendulum on a cart
Trying out a reinforcement learning algorithm that uses predictions of future states
Sample efficient model based RL algorithm
Scripts, data and tasks for running the analyses as described in https://psyarxiv.com/ervsb/
Simple Muesli RL algorithm implementation (PyTorch)
Example MBPO implementation with ReLAx
This presentation contains very precise yet detailed explanation of concepts of a very interesting topic -- Reinforcement Learning.
Planning from Pixels with PlaNet
Zero-trial Model-based Imitation Learning with Partial Trajectory
Behaviour Cloning of Cartpole Swing-up Policy with Model-Predictive Uncertainty Regularization (UW CSE571 Guided Project)
This is the official PyTorch implementation of my Master thesis. The main goal of this work was to optimize latent dynamics models with unsupervised representation learning.
VQ-VAE-based image tokenizer for model-based RL
A multi-agent deep reinforcement learning model to de-traffic our lives
RLFlow: Optimising Neural Network Subgraph Transformation with World Models
Add a description, image, and links to the model-based-rl topic page so that developers can more easily learn about it.
To associate your repository with the model-based-rl topic, visit your repo's landing page and select "manage topics."