Alternatives and similar repositories for aop

Users that are interested in aop are comparing it to the libraries listed below

• behaviorguidedRL / BGRL
  Open source demo for the paper Learning to Score Behaviors for Guided Policy Optimization
  ☆24Updated 5 years ago
• manantomar / Mirror-Descent-Policy-Optimization
  Mirror Descent Policy Optimization
  ☆41Updated 5 years ago
• liziniu / HyperDQN
  Code for ICLR 2022 Paper (HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning)
  ☆12Updated 2 years ago
• uncharted-technologies / risk-and-uncertainty
  Code that can be used to reproduce the experiments in our paper "Estimating Risk and Uncertainty in Deep Reinforcement Learning"
  ☆31Updated 3 years ago
• causal-rl-anonymous / causal-rl
  ☆48Updated 3 years ago
• IBM / constrained-rl
  Constrained Exploration and Recovery from Experience Shaping
  ☆22Updated 6 years ago
• gyh75520 / Relational_DRL
  Implementation of Relational Deep Reinforcement Learning
  ☆25Updated 5 years ago
• polixir / causal-mbrl
  Toolkit of Causal Model-based Reinforcement Learning.
  ☆32Updated 2 years ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆47Updated 4 years ago
• XinJingHao / Actor-Sharer-Learner
  Actor-Sharer-Learner training framework for off-policy DRL algorithms
  ☆21Updated 11 months ago
• montrealrobotics / iv_rl
  IV-RL - Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation
  ☆40Updated 5 months ago
• Cranial-XIX / metric-residual-network
  Official PyTorch Implementation for Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning
  ☆19Updated 2 years ago
• ben-eysenbach / mnm
  Code to accompany the paper "Mismatched No More: Joint Model-Policy Optimization for Model-Based RL"
  ☆20Updated 4 years ago
• icaros-usc / dqd-rl
  Official implementation of "Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learning"
  ☆21Updated 3 years ago
• sisl / MPHRL
  Model Primitive Hierarchical Reinforcement Learning
  ☆13Updated 3 years ago
• jonasrothfuss / model_ensemble_meta_learning
  Implementation of the Model-Based Meta-Policy-Optimization (MB-MPO) algorithm
  ☆44Updated 7 years ago
• dannysdeng / dqn-pytorch
  PyTorch - Implicit Quantile Networks - Quantile Regression - C51
  ☆22Updated 6 years ago
• apexrl / autombpo
  Implementation of NeurIPS2021 paper <On Effective Scheduling of Model-based Reinforcement Learning>
  ☆13Updated 4 years ago
• ElisevanderPol / mdp-homomorphic-networks
  ☆30Updated 4 years ago
• jparkerholder / DvD_ES
  Code from the paper "Effective Diversity in Population Based Reinforcement Learning", presented as a spotlight at NeurIPS 2020. This is t…
  ☆44Updated 5 years ago
• ben-eysenbach / info_geometry
  Code to accompany the paper "The Information Geometry of Unsupervised Reinforcement Learning"
  ☆20Updated 4 years ago
• ermongroup / CalibratedModelBasedRL
  Code for "Calibrated Model-Based Deep Reinforcement Learning", ICML 2019.
  ☆55Updated 6 years ago
• rail-berkeley / design-bench
  ☆53Updated 3 years ago
• lmzintgraf / hyperx
  ☆17Updated 3 years ago
• ketatam / Exploring-Munchausen-Reinforcement-Learning
  PyTorch implementation of Munchausen Reinforcement Learning based on DQN and SAC. Handles discrete and continuous action spaces
  ☆15Updated 4 years ago
• philipjball / ReadyPolicyOne
  🔍 Codebase for the ICML '20 paper "Ready Policy One: World Building Through Active Learning" (arxiv: 2002.02693)
  ☆18Updated 2 years ago
• kzl / lifelong_rl
  Pytorch implementations of RL algorithms, focusing on model-based, lifelong, reset-free, and offline algorithms. Official codebase for Re…
  ☆108Updated 3 years ago
• xingchenwan / bgpbt
  [AutoML'22] Bayesian Generational Population-based Training (BG-PBT)
  ☆29Updated 3 years ago
• microsoft / logrl
  Logarithmic Reinforcement Learning
  ☆28Updated 2 years ago
• zdhNarsil / Stochastic-Marginal-Actor-Critic
  Official pytorch implementation for our ICLR 2023 paper "Latent State Marginalization as a Low-cost Approach for Improving Exploration".
  ☆24Updated 2 years ago