All Projects → transedward → pytorch-hdqn

transedward / pytorch-hdqn

Licence: other
Hierarchical-DQN in pytorch (not actively maintained)

Programming Languages

Jupyter Notebook
11667 projects
python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to pytorch-hdqn

rl implementations
No description or website provided.
Stars: ✭ 40 (+11.11%)
Mutual labels:  deep-reinforcement-learning, hierarchical-reinforcement-learning
reinforcement-learning-papers
My notes on reinforcement learning papers
Stars: ✭ 13 (-63.89%)
Mutual labels:  deep-reinforcement-learning, hierarchical-reinforcement-learning
RL
Reinforcement Learning Demos
Stars: ✭ 66 (+83.33%)
Mutual labels:  deep-reinforcement-learning
Explorer
Explorer is a PyTorch reinforcement learning framework for exploring new ideas.
Stars: ✭ 54 (+50%)
Mutual labels:  deep-reinforcement-learning
pokeai
Develop ultimate AI Pokémon trainer
Stars: ✭ 18 (-50%)
Mutual labels:  deep-reinforcement-learning
neural-mpc
No description or website provided.
Stars: ✭ 54 (+50%)
Mutual labels:  deep-reinforcement-learning
rtrl
PyTorch implementation of our paper Real-Time Reinforcement Learning (NeurIPS 2019)
Stars: ✭ 57 (+58.33%)
Mutual labels:  deep-reinforcement-learning
MP-DQN
Source code for the dissertation: "Multi-Pass Deep Q-Networks for Reinforcement Learning with Parameterised Action Spaces"
Stars: ✭ 99 (+175%)
Mutual labels:  deep-reinforcement-learning
Smart-Traffic-Signals-in-India-using-Deep-Reinforcement-Learning-and-Advanced-Computer-Vision
We have used Deep Reinforcement Learning and Advanced Computer Vision techniques to for the creation of Smart Traffic Signals for Indian Roads. We have created the scripts for using SUMO as our environment for deploying all our RL models.
Stars: ✭ 131 (+263.89%)
Mutual labels:  deep-reinforcement-learning
godpaper
🐵 An AI chess-board-game framework(by many programming languages) implementations.
Stars: ✭ 40 (+11.11%)
Mutual labels:  deep-reinforcement-learning
Underflow
With underflow, create trafic light clusters that interact together to regulate circulation
Stars: ✭ 12 (-66.67%)
Mutual labels:  deep-reinforcement-learning
drl grasping
Deep Reinforcement Learning for Robotic Grasping from Octrees
Stars: ✭ 160 (+344.44%)
Mutual labels:  deep-reinforcement-learning
AI booklet CE-AUT
Booklet and exam of Artificial Intelligence Master Degree at Amirkabir University of technology.
Stars: ✭ 14 (-61.11%)
Mutual labels:  deep-reinforcement-learning
racing dreamer
Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing
Stars: ✭ 31 (-13.89%)
Mutual labels:  deep-reinforcement-learning
muzero
A clean implementation of MuZero and AlphaZero following the AlphaZero General framework. Train and Pit both algorithms against each other, and investigate reliability of learned MuZero MDP models.
Stars: ✭ 126 (+250%)
Mutual labels:  deep-reinforcement-learning
HRAC
PyTorch code accompanying the paper "Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning" (NeurIPS 2020).
Stars: ✭ 21 (-41.67%)
Mutual labels:  hierarchical-reinforcement-learning
CrowdNav DSRNN
[ICRA 2021] Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning
Stars: ✭ 43 (+19.44%)
Mutual labels:  deep-reinforcement-learning
datascience-mashup
In this repo I will try to gather all of the projects related to data science with clean datasets and high accuracy models to solve real world problems.
Stars: ✭ 36 (+0%)
Mutual labels:  deep-reinforcement-learning
AutoPentest-DRL
AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning
Stars: ✭ 196 (+444.44%)
Mutual labels:  deep-reinforcement-learning
Reinforcement Learning Course
Curso de Aprendizaje por Refuerzo, de 0 a 100 con notebooks y slides muy sencillas para entenderlo todo perfectamente.
Stars: ✭ 18 (-50%)
Mutual labels:  deep-reinforcement-learning

pytorch-hDQN

hierarchical-DQN in pytorch. [paper]

Results

Only Q-learning and h-DQN for StochasticMDPEnv are implemented.

Q-Learning for Experiment 1 (Discrete stochastic decision process)

Rewards

Visited States

h-DQN for Experiment 1 (Discrete stochastic decision process)

Rewards

Visited States

Reference

https://github.com/EthanMacdonald/h-DQN: Another implementation of hierarchical-DQN paper, which I copied the StochasticMDPEnv from.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].