nnaisense / 2017-learning-to-runView external linksLinks
The Winning Solution for the Learning To Run Challenge 2017
☆60Jul 4, 2018Updated 7 years ago
Alternatives and similar repositories for 2017-learning-to-run
Users that are interested in 2017-learning-to-run are comparing it to the libraries listed below
Sorting:
- NIPS2017 challenge☆49Oct 7, 2018Updated 7 years ago
- Reason8.ai PyTorch solution for NIPS RL 2017 challenge☆84Oct 15, 2019Updated 6 years ago
- 2nd place solution of NIPS2017 LearningToRun Competition.☆130May 29, 2022Updated 3 years ago
- Helper for NeurIPS 2018 Challenge: AI for Prosthetics☆39Sep 27, 2018Updated 7 years ago
- Reinforcement learning environments with musculoskeletal models☆942Jan 24, 2022Updated 4 years ago
- Avoiding catastrophic failures in reinforcement learning by learning to shape rewards.☆10Nov 13, 2017Updated 8 years ago
- PhD Publications and Thesis on LASSO Model Predictive Control☆20Jun 2, 2019Updated 6 years ago
- OpenAI Gym environment for DART robotics simulator.☆22Apr 17, 2018Updated 7 years ago
- Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning☆16Nov 7, 2018Updated 7 years ago
- Decoupling Dynamics and Reward for Transfer Learning☆16Sep 7, 2018Updated 7 years ago
- Code Released for NeurIPS 2018 paper: Synthesized Policies for Transfer and Adaptation across Tasks and Environments☆16Apr 17, 2019Updated 6 years ago
- Code to reproduce Supervised Policy Update (ICLR 2019)☆17Dec 8, 2022Updated 3 years ago
- Starter kit for getting started in the NIPS 2017 Criteo Ad Placement Challenge☆18Nov 10, 2017Updated 8 years ago
- starter kit for vizdoom2018-singleplayer track☆28Jul 29, 2018Updated 7 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆20Jan 11, 2019Updated 7 years ago
- Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees☆93Sep 13, 2019Updated 6 years ago
- Code to reproduce the results of "Curiosity Driven Exploration of Learned Disentangled Goal Spaces"☆19Oct 26, 2018Updated 7 years ago
- Code for reproducing experiments in Model-Based Active Exploration, ICML 2019☆81Jul 23, 2019Updated 6 years ago
- Our NIPS 2017: Learning to Run source code☆55Mar 31, 2023Updated 2 years ago
- Trust Region Policy Optimization with TensorFlow and OpenAI Gym☆361Jun 2, 2020Updated 5 years ago
- Implementation of Receding Horizon Curiosity Algrithm☆13Mar 24, 2023Updated 2 years ago
- yet another DL framework☆11Oct 28, 2018Updated 7 years ago
- Match Selection and Refinement for Accurate Structure from Motion☆12Oct 26, 2014Updated 11 years ago
- A tiny reinforcement learning codebase for continuous control, built on top of JAX.☆15Mar 28, 2023Updated 2 years ago
- Implicit Differentiable Optimal Control (IDOC) with JAX☆12May 11, 2022Updated 3 years ago
- Stochastic Machines for Unsupervised Learning implemented in Pytorch.☆10Sep 3, 2017Updated 8 years ago
- my Reinforcement Learning playground☆10Oct 7, 2018Updated 7 years ago
- Process time series data with Redis and Kafka☆10May 21, 2021Updated 4 years ago
- Code for Environment Probing Interaction Policies [ICLR 2019]☆29Jun 17, 2019Updated 6 years ago
- Distributed Rainbow-IQN for Atari☆80Dec 17, 2019Updated 6 years ago
- Reinforcement Learning program that looks to be able to quickly learn to solve a Rubik's Cube☆15Jun 22, 2021Updated 4 years ago
- ☆54Feb 28, 2024Updated last year
- Guided Evolutionary Strategies☆273Apr 6, 2023Updated 2 years ago
- Code for experimenting with state and action abstractions in reinforcement learning.☆30Dec 11, 2020Updated 5 years ago
- Code for "Calibrated Model-Based Deep Reinforcement Learning", ICML 2019.☆55May 15, 2019Updated 6 years ago
- A collection of code investigating the use of information theory for abstractions in RL☆16Nov 14, 2018Updated 7 years ago
- Codebase of Santara et. al., RAIL: Risk Averse Imitation Learning, Published in AAMAS 2018☆15Jan 15, 2022Updated 4 years ago
- Pytorch implementation of LOLA (https://arxiv.org/abs/1709.04326) using DiCE (https://arxiv.org/abs/1802.05098)☆96Aug 21, 2018Updated 7 years ago
- This repo replicates the results Horgan et al obtained in "Distributed Prioritized Experience Replay"☆190Mar 18, 2019Updated 6 years ago