GhadaSokar / Dynamic-Sparse-Training-for-Deep-Reinforcement-LearningLinks
[IJCAI 2022] "Dynamic Sparse Training for Deep Reinforcement Learning" by Ghada Sokar, Elena Mocanu , Decebal Constantin Mocanu, Mykola Pechenizkiy, and Peter Stone.
☆13Updated 3 years ago
Alternatives and similar repositories for Dynamic-Sparse-Training-for-Deep-Reinforcement-Learning
Users that are interested in Dynamic-Sparse-Training-for-Deep-Reinforcement-Learning are comparing it to the libraries listed below
Sorting:
- Constrained Exploration and Recovery from Experience Shaping☆22Updated 6 years ago
- Evolution-based Soft Actor-Critic (ESAC)☆42Updated last year
- Experiments to train transformer network to master reinforcement learning environments.☆32Updated 4 years ago
- PyTorch implementation of D4PG with the SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2R…☆23Updated 4 years ago
- The implementation of Discriminator Soft Actor Critic☆15Updated 5 years ago
- DecentralizedLearning☆25Updated 2 years ago
- Attention-based Curiosity-driven Exploration in Deep Reinforcement Learning☆27Updated 5 years ago
- Code accompanying the paper "Action Robust Reinforcement Learning and Applications in Continuous Control" https://arxiv.org/abs/1901.0918…☆48Updated 6 years ago
- Code for the paper "D2RL: Deep Dense Architectures for Reinforcement Learning"☆40Updated 4 years ago
- Open source demo for the paper Learning to Score Behaviors for Guided Policy Optimization☆24Updated 5 years ago
- MARS is shortened for Multi-Agent Research Studio, a library for mulit-agent reinforcement learning research.☆48Updated last year
- Code for the paper "AlwaysSafe: Reinforcement Learning Without Safety Constraint Violations During Training"☆17Updated 3 years ago
- Our version of #Exploration: A Study of Count-Based Explorationfor Deep Reinforcement Learning for a class project☆16Updated 4 years ago
- Model-based reinforcement learning using CEM, MPC and PETS☆16Updated 5 years ago
- Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020☆32Updated 4 years ago
- Experiment code for testing effect of various action space transformations in reinforcement learning☆30Updated 5 years ago
- Hierarchical Reinforcement Learning (batteries included)☆46Updated 5 years ago
- on-policy optimization baselines for deep reinforcement learning☆30Updated 5 years ago
- Implementations of a large collection of reinforcement learning algorithms.☆28Updated last year
- Robust Multi-Agent Reinforcement Learning with State Uncertainty☆13Updated 2 years ago
- ☆22Updated last year
- ☆10Updated 5 years ago
- An unofficial implementation for online decision transformer☆40Updated 2 years ago
- Pytorch implementation of "Maximum a Posteriori Policy Optimization" with Retrace for Discrete gym environments☆27Updated 4 years ago
- Multi-Agent training using Deep Deterministic Policy Gradient Networks, Solving the Tennis Environment☆11Updated 6 years ago
- ☆17Updated 4 years ago
- Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning (NeurIPS 2020)☆39Updated 4 years ago
- Codes accompanying the paper "DOP: Off-Policy Multi-Agent Decomposed Policy Gradients" (ICLR 2021, https://arxiv.org/abs/2007.12322)☆51Updated 2 years ago
- Count based exploration with the successor representation for Unity ML's Pyramid☆12Updated 6 years ago
- Improving upon state of the art cooperative deep reinforcement learning in StarCraft II☆13Updated 6 years ago