Alternatives and similar repositories for e-maml

Users that are interested in e-maml are comparing it to the libraries listed below

• llan-ml / tesp
  Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"
  ☆34Updated 6 years ago
• deep-skill-chaining / deep-skill-chaining
  Implementation of the skill discovery algorithm described in ICLR submission "Option Discovery using Deep Skill Chaining"
  ☆28Updated 5 years ago
• russellmendonca / maesn_suite
  ☆43Updated 6 years ago
• Hwhitetooth / lirpg
  ☆61Updated 7 years ago
• rraileanu / idaac
  ☆53Updated last year
• dennisl88 / rand_param_envs
  Random parameter environments using gym 0.7.4 and mujoco-py 0.5.7
  ☆20Updated 6 years ago
• Ji4chenLi / Multi-Task-Batch-RL
  ☆26Updated 2 years ago
• kkhetarpal / ioc
  Options of Interest: Temporal Abstraction with Interest Functions AAAI 2020
  ☆25Updated 4 years ago
• uber-research / D3G
  Estimating Q(s,s') with Deep Deterministic Dynamics Gradients
  ☆32Updated 5 years ago
• YYCAAA / V-MPO_Lunarlander
  Simple implementation of V-MPO proposed in https://arxiv.org/abs/1909.12238
  ☆47Updated 4 years ago
• facebookresearch / icp-block-mdp
  Invariant Causal Prediction for Block MDPs
  ☆44Updated 5 years ago
• victorcampos7 / edl
  Code for "Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills"
  ☆37Updated 5 years ago
• mcmachado / count_based_exploration_sr
  ☆31Updated 5 years ago
• suyoung-lee / Episodic-Backward-Update
  Implementation of "Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update", NeurIPS 2019.
  ☆17Updated 5 years ago
• YuejiangLIU / prioritized_option_critic
  Implementation of the Prioritized Option-Critic on the Four-Rooms Environment
  ☆16Updated 7 years ago
• clvrai / new-actions-rl
  ☆24Updated 10 months ago
• robintyh1 / onpolicybaselines
  on-policy optimization baselines for deep reinforcement learning
  ☆30Updated 5 years ago
• facebookresearch / level-replay
  This code implements Prioritized Level Replay, a method for sampling training levels for reinforcement learning agents that exploits the …
  ☆86Updated 4 years ago
• ruizhaogit / mep
  Maximum Entropy-Regularized Multi-Goal Reinforcement Learning (ICML 2019)
  ☆23Updated 6 years ago
• RomainLaroche / SPIBB
  Safe Policy Improvement with Baseline Bootstrapping
  ☆26Updated 5 years ago
• RLAgent / state-marginal-matching
  Efficient Exploration via State Marginal Matching (2019)
  ☆69Updated 5 years ago
• microsoft / oac-explore
  Code accompanying the paper "Better Exploration with Optimistic Actor Critic" (NeurIPS 2019)
  ☆70Updated last year
• younggyoseo / RE3
  RE3: State Entropy Maximization with Random Encoders for Efficient Exploration
  ☆68Updated 3 years ago
• xkianteb / dril
  Disagreement-Regularized Imitation Learning
  ☆30Updated 4 years ago
• bhairavmehta95 / data-efficient-hrl
  Implementation of Data Efficient Reinforcement Learning in Pytorch
  ☆20Updated 5 years ago
• eugenevinitsky / robust_RL_multi_adversary
  We investigate the effect of populations on finding good solutions to the robust MDP
  ☆28Updated 4 years ago
• rraileanu / policy-dynamics-value-functions
  ☆32Updated 9 months ago
• alexlioralexli / rllab-finetuning
  ☆29Updated 2 years ago
• tesslerc / GAC
  Code accompanying NeurIPS 2019 paper: "Distributional Policy Optimization - An Alternative Approach for Continuous Control"
  ☆22Updated 5 years ago
• mklissa / PPOC
  Proximal Policy Option-Critic
  ☆23Updated 6 years ago