Alternatives and similar repositories for COBS

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

• google-research / deep_ope
  ☆86Updated 10 months ago
• SwapnilPande / MOReL
  Model-Based Offline Reinforcement Learning
  ☆50Updated 4 years ago
• davidbrandfonbrener / onestep-rl
  ☆42Updated 3 years ago
• yifan12wu / rl-laplacian
  Learning Laplacian Representations in Reinforcement Learning
  ☆17Updated 4 years ago
• robintyh1 / onpolicybaselines
  on-policy optimization baselines for deep reinforcement learning
  ☆30Updated 5 years ago
• dennisl88 / rand_param_envs
  Random parameter environments using gym 0.7.4 and mujoco-py 0.5.7
  ☆20Updated 6 years ago
• rraileanu / idaac
  ☆53Updated last year
• facebookresearch / icp-block-mdp
  Invariant Causal Prediction for Block MDPs
  ☆44Updated 4 years ago
• wangzizhao / CausalDynamicsLearning
  ☆31Updated 2 years ago
• tianheyu927 / mopo
  Code for MOPO: Model-based Offline Policy Optimization
  ☆179Updated 3 years ago
• Baichenjia / PBRL
  Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning
  ☆28Updated 3 years ago
• google-research / dice_rl
  ☆104Updated 9 months ago
• facebookresearch / level-replay
  This code implements Prioritized Level Replay, a method for sampling training levels for reinforcement learning agents that exploits the …
  ☆86Updated 3 years ago
• Hwhitetooth / lirpg
  ☆61Updated 6 years ago
• ahmed-touati / controllable_agent
  ☆45Updated last year
• justinjfu / diagnosing_qlearning
  Code for Diagnosing Bottlenecks in Deep Q-learning. Contains implementations of tabular environments plus solvers.
  ☆19Updated 6 years ago
• young-geng / JaxCQL
  Conservative Q learning in Jax
  ☆54Updated 2 years ago
• spitis / mrl
  ☆112Updated 2 years ago
• stratisMarkou / sample-efficient-bayesian-rl
  Source for the sample efficient tabular RL submission to the 2019 NIPS workshop on Biological and Artificial RL
  ☆25Updated 3 years ago
• yudasong / HyQ
  Official code repo for paper: Hybrid RL: Using both offline and online data can make RL efficient.
  ☆24Updated 2 years ago
• mcmachado / count_based_exploration_sr
  ☆31Updated 5 years ago
• clvoloshin / constrained_batch_policy_learning
  ☆26Updated 5 years ago
• nuria95 / O-RAAC
  Offline Risk-Averse Actor-Critic (O-RAAC). A model-free RL algorithm for risk-averse RL in a fully offline setting
  ☆35Updated 4 years ago
• Ji4chenLi / Multi-Task-Batch-RL
  ☆26Updated 2 years ago
• zafarali / emdp
  Easy MDPs and grid worlds with accessible transition dynamics to do exact calculations
  ☆49Updated 3 years ago
• dido1998 / CausalMBRL
  Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
  ☆48Updated 3 years ago
• ml-jku / rudder-demonstration-code
  Code for demonstration example-task in RUDDER blog
  ☆23Updated 5 years ago
• Wenxuan-Zhou / PLAS
  Code for Latent Action Space for Offline Reinforcement Learning [CoRL 2020]
  ☆53Updated 3 years ago
• causal-rl-anonymous / causal-rl
  ☆43Updated 3 years ago
• eric-mitchell / macaw
  Code for "Offline Meta-Reinforcement Learning with Advantage Weighting" [ICML 2021]
  ☆47Updated 2 years ago