Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch
☆880Dec 27, 2022Updated 3 years ago
Alternatives and similar repositories for pytorch-maml-rl
Users that are interested in pytorch-maml-rl are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Code for RL experiments in "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"☆669Jan 19, 2023Updated 3 years ago
- Implementation of Proximal Meta-Policy Search (ProMP) as well as related Meta-RL algorithm. Includes a useful experiment framework for Me…☆248Sep 30, 2022Updated 3 years ago
- Implementation of Efficient Off-policy Meta-learning via Probabilistic Context Variables (PEARL)☆507Dec 1, 2022Updated 3 years ago
- Learning to Adapt in Dynamic, Real-World Environment through Meta-Reinforcement Learning☆218Dec 27, 2022Updated 3 years ago
- PyTorch implementation of MAML: https://arxiv.org/abs/1703.03400☆567Oct 4, 2018Updated 7 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"☆2,727Jan 19, 2020Updated 6 years ago
- Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)☆2,480May 16, 2019Updated 7 years ago
- Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning☆1,821May 17, 2026Updated last week
- Collection of reinforcement learning algorithms☆2,901Jun 17, 2024Updated last year
- A PyTorch Library for Meta-learning Research☆2,882Dec 16, 2025Updated 5 months ago
- PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinfor…☆3,901May 29, 2022Updated 3 years ago
- Taming MAML: efficient unbiased meta-reinforcement learning☆30Sep 30, 2022Updated 3 years ago
- ☆44Oct 27, 2018Updated 7 years ago
- Implementation of Meta-RL A3C algorithm☆407Feb 22, 2017Updated 9 years ago
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- Reinforcement Learning in PyTorch☆2,275Jan 4, 2021Updated 5 years ago
- Code for the paper "Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments"☆309Apr 13, 2023Updated 3 years ago
- A toolkit for reproducible reinforcement learning research.☆2,101May 4, 2023Updated 3 years ago
- Code for the paper "Meta-Q-Learning"( ICLR 2020)☆108Jun 18, 2022Updated 3 years ago
- ☆10Aug 8, 2021Updated 4 years ago
- The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) p…☆827Dec 5, 2023Updated 2 years ago
- Code for "Fast Context Adaptation via Meta-Learning"☆145Mar 22, 2021Updated 5 years ago
- An Implementation of Model-Agnostic Meta-Learning in PyTorch with Torchmeta☆240Jul 7, 2020Updated 5 years ago
- Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"☆475Jul 6, 2023Updated 2 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- ☆20Feb 8, 2023Updated 3 years ago
- A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch☆2,058Jul 17, 2023Updated 2 years ago
- lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.☆378Nov 19, 2022Updated 3 years ago
- ICML 2018 Self-Imitation Learning☆276Apr 18, 2020Updated 6 years ago
- ☆399Jul 18, 2019Updated 6 years ago
- A collection of Meta-Reinforcement Learning algorithms in PyTorch☆51Jul 16, 2024Updated last year
- My implementations of 'RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning' and 'A Simple Neural Attentive Meta-Learner'☆71Jan 1, 2022Updated 4 years ago
- Benchmark present methods for efficient reinforcement learning. Methods include Reptile, MAML, Residual Policy, etc. RL algorithms includ…☆32Jan 19, 2023Updated 3 years ago
- Implementation of Model-Agnostic Meta-Learning (MAML) applied on Reinforcement Learning problems in TensorFlow 2.☆27May 11, 2021Updated 5 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- ☆33Jun 16, 2023Updated 2 years ago
- A PyTorch implementation of OpenAI's REPTILE algorithm☆219Dec 31, 2019Updated 6 years ago
- A simple RNN meta-learner☆10Dec 17, 2018Updated 7 years ago
- A PyTorch Library for Reinforcement Learning Research☆198Jun 22, 2025Updated 11 months ago
- rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.☆3,060Jun 10, 2023Updated 2 years ago
- PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Lear…☆1,284Feb 9, 2021Updated 5 years ago
- Code for the paper "On First-Order Meta-Learning Algorithms"☆1,039May 20, 2023Updated 3 years ago