jonasrothfuss / model_ensemble_meta_learning
Implementation of the Model-Based Meta-Policy-Optimization (MB-MPO) algorithm
β44Updated 6 years ago
Alternatives and similar repositories for model_ensemble_meta_learning:
Users that are interested in model_ensemble_meta_learning are comparing it to the libraries listed below
- β97Updated last year
- on-policy optimization baselines for deep reinforcement learningβ29Updated 4 years ago
- π΄ OffCon^3: SOTA PyTorch SAC and TD3 Implementations (arxiv: 2101.11331)β24Updated 3 years ago
- IV-RL - Sample Efficient Deep Reinforcement Learning via Uncertainty Estimationβ40Updated 4 months ago
- Learning Action-Value Gradients in Model-based Policy Optimizationβ31Updated 3 years ago
- Estimating Q(s,s') with Deep Deterministic Dynamics Gradientsβ32Updated 5 years ago
- Easy MDPs and grid worlds with accessible transition dynamics to do exact calculationsβ49Updated 2 years ago
- β30Updated last year
- Codes for the study "Variational Recurrent Models for Solving Partially Observable Control Tasks", published as a conference paper at ICLβ¦β53Updated 4 years ago
- β82Updated 3 years ago
- Code for "Calibrated Model-Based Deep Reinforcement Learning", ICML 2019.β55Updated 5 years ago
- Safe Option-Critic: Learning Safety in the Option-Critic Architectureβ20Updated 6 years ago
- MetaGenRL, a novel meta reinforcement learning algorithm. Unlike prior work, MetaGenRL can generalize to new environments that are entireβ¦β67Updated 4 years ago
- On the model-based stochastic value gradient for continuous reinforcement learningβ55Updated last year
- Implementation of the skill discovery algorithm described in ICLR submission "Option Discovery using Deep Skill Chaining"β28Updated 5 years ago
- Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"β34Updated 5 years ago
- π§Ά Minimal PyTorch Soft Actor Critic (SAC) implementationβ38Updated 3 years ago
- Maximum Entropy-Regularized Multi-Goal Reinforcement Learning (ICML 2019)β23Updated 5 years ago
- Safe Policy Improvement with Baseline Bootstrappingβ26Updated 4 years ago
- Open source demo for the paper Learning to Score Behaviors for Guided Policy Optimizationβ24Updated 4 years ago
- β60Updated 6 years ago
- E-MAML, and RL-MAML baseline implemented in Tensorflow v1β16Updated 5 years ago
- This code implements Prioritized Level Replay, a method for sampling training levels for reinforcement learning agents that exploits the β¦β83Updated 3 years ago
- A Tensorflow implementation of the Option-Critic Architectureβ71Updated 7 years ago
- LAMBDA is a model-based reinforcement learning agent that uses Bayesian world models for safe policy optimizationβ34Updated 2 years ago
- Recurrent continuous reinforcement learning algorithms implemented in Pytorch.β50Updated 3 years ago
- Pytorch implementations of RL algorithms, focusing on model-based, lifelong, reset-free, and offline algorithms. Official codebase for Reβ¦β104Updated 3 years ago
- β18Updated 4 years ago
- PyTorch - Implicit Quantile Networks - Quantile Regression - C51β23Updated 5 years ago
- Disagreement-Regularized Imitation Learningβ30Updated 3 years ago