Official code for "RAMBO: Robust Adversarial Model-Based Offline RL", NeurIPS 2022
☆33Jun 2, 2023Updated 3 years ago
Alternatives and similar repositories for rambo
Users that are interested in rambo 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 NeurIPS 2021 paper "Offline Reinforcement Learning with Reverse Model-based Imagination"☆20Dec 22, 2021Updated 4 years ago
- An elegant PyTorch offline reinforcement learning library for researchers.☆393Aug 9, 2026Updated 3 weeks ago
- Code for MOBILE: Model-Bellman Inconsistency Penalized Offline Policy Optimization☆22Apr 17, 2024Updated 2 years ago
- We investigate the effect of populations on finding good solutions to the robust MDP☆29Mar 27, 2021Updated 5 years ago
- Code accompanying the paper "Action Robust Reinforcement Learning and Applications in Continuous Control" https://arxiv.org/abs/1901.0918…☆49Apr 14, 2019Updated 7 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- This repository contains the official code for our NeurIPS 2021 publication "Robust Deep Reinforcement Learning through Adversarial Loss…☆33Jan 21, 2022Updated 4 years ago
- Generalized Decision Transformer for Offline Hindsight Information Matching (ICLR2022)☆70Aug 8, 2022Updated 4 years ago
- Robust Reinforcement Learning with the Alternating Training of Learned Adversaries (ATLA) framework☆70Jan 26, 2021Updated 5 years ago
- Code for Tackling Long-Horizon Tasks with Model-based Offline Reinforcement Learning☆19Feb 6, 2025Updated last year
- [ICML 2022] Robust Deep Reinforcement Learning through Bootstrapped Opportunistic Curriculum☆12Jul 15, 2022Updated 4 years ago
- Implementation and evaluation of Almanac (Automaton/Logic Multi-Agent Natural Actor-Critic), an algorithm for multi-agent reinforcement l…☆10May 5, 2022Updated 4 years ago
- Code accompanying the paper Adversarially Trained Actor Critic for Offline Reinforcement Learning by Ching-An Cheng*, Tengyang Xie*, Nan …☆74Feb 2, 2023Updated 3 years ago
- [NeurIPS 2020, Spotlight] Code for "Robust Deep Reinforcement Learning against Adversarial Perturbations on Observations"☆145Nov 16, 2021Updated 4 years ago
- Policy Transfer across Visual and Dynamics Domain Gaps via Iterative Grounding (RSS 2021)☆12Oct 22, 2021Updated 4 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Official code for "World Models via Policy-Guided Trajectory Diffusion", TMLR 2024☆77Mar 22, 2024Updated 2 years ago
- Code to accompany the paper "Mismatched No More: Joint Model-Policy Optimization for Model-Based RL"☆21Oct 6, 2021Updated 4 years ago
- ☆12Apr 25, 2022Updated 4 years ago
- Code to reproduce results from the paper: Prediction and Control in Continual Reinforcement Learning, NeurIPS 2023.☆13May 10, 2024Updated 2 years ago
- Official repo for Offline RL for Online RL☆18Oct 14, 2023Updated 2 years ago
- re-implementation of the offline model-based RL algorithm MOPO in pytorch☆26Feb 28, 2022Updated 4 years ago
- Contains implementation of the DoubIL and ResiduIL algorithms from the ICML '22 paper Causal Imitation Learning under Temporally Correlat…☆11Dec 9, 2022Updated 3 years ago
- Code to accompany the paper "The Information Geometry of Unsupervised Reinforcement Learning"☆20Oct 6, 2021Updated 4 years ago
- ☆10Oct 11, 2022Updated 3 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code☆17Aug 23, 2024Updated 2 years ago
- Code for the paper: Causal Action Influence Aware Counterfactual Data Augmentation @ICML2024☆13Jul 19, 2024Updated 2 years ago
- Python interface for accessing the near real-world offline reinforcement learning (NeoRL) benchmark datasets☆137Nov 21, 2024Updated last year
- ExORL: Exploratory Data for Offline Reinforcement Learning☆139Feb 8, 2022Updated 4 years ago
- [NeurIPS 2025] BOOM, A Planning-driven Model-Based RL algorithm☆61Apr 23, 2026Updated 4 months ago
- Implementation of CoDAIL in the ICLR 2020 paper <Multi-Agent Interactions Modeling with Correlated Policies>☆19Jun 17, 2021Updated 5 years ago
- ☆15Oct 20, 2020Updated 5 years ago
- Official code for ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning (AAAI'24)☆16Feb 10, 2024Updated 2 years ago
- Model-Based Offline Reinforcement Learning☆51Jan 13, 2021Updated 5 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- RLHF-Blender: A Configurable Interactive Interface for Learning from Diverse Human Feedback☆14May 19, 2026Updated 3 months ago
- Official PyTorch implementation of "ACE:Off-Policy Actor-Critic with Causality-Aware Entropy Regularization"☆35May 13, 2024Updated 2 years ago
- Official code for the ICLR 2025 paper, "Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining"☆30Dec 1, 2024Updated last year
- [ICLR 2024 Spotlight] Code for ICLR 2024 paper "Towards Robust Offline Reinforcement Learning under Diverse Data Corruption"☆22Nov 25, 2024Updated last year
- Official implementation of the paper: Safe Model-Based Reinforcement Learning with an Uncertainty-Aware Reachability Certificate☆25Dec 4, 2023Updated 2 years ago
- [NeurIPS'22 Spotlight] When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning☆59Sep 24, 2023Updated 2 years ago
- Official Codebase for Offline Reinforcement Learning from Images with Latent Space Models☆31Apr 30, 2021Updated 5 years ago