Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation
Suraj Nair and Chelsea Finn
Paper: https://arxiv.org/abs/1909.05829
Code: https://github.com/google-research/google-research/tree/master/hierarchical_foresight
#MachineLearning #ArtificialIntelligence #Robotics #ReinforcementLearning
Suraj Nair and Chelsea Finn
Paper: https://arxiv.org/abs/1909.05829
Code: https://github.com/google-research/google-research/tree/master/hierarchical_foresight
#MachineLearning #ArtificialIntelligence #Robotics #ReinforcementLearning
Deep Dynamics Models for Learning Dexterous Manipulation
Nagabandi et al.: https://arxiv.org/abs/1909.11652
#Robotics #MachineLearning #ReinforcementLearning
Nagabandi et al.: https://arxiv.org/abs/1909.11652
#Robotics #MachineLearning #ReinforcementLearning
arXiv.org
Deep Dynamics Models for Learning Dexterous Manipulation
Dexterous multi-fingered hands can provide robots with the ability to flexibly perform a wide range of manipulation skills. However, many of the more complex behaviors are also notoriously...
End-to-End Motion Planning of Quadrotors Using Deep Reinforcement Learning
Efe Camci and Erdal Kayacan : https://arxiv.org/abs/1909.13599
#Robotics #ArtificialIntelligence #ReinforcementLearning
Efe Camci and Erdal Kayacan : https://arxiv.org/abs/1909.13599
#Robotics #ArtificialIntelligence #ReinforcementLearning
Bayesian Optimization Meets Riemannian Manifolds in Robot Learning
Jaquier et al.: https://arxiv.org/abs/1910.04998
#BayesianOptimization #Robotics #MachineLearning
Jaquier et al.: https://arxiv.org/abs/1910.04998
#BayesianOptimization #Robotics #MachineLearning
Quantized Reinforcement Learning (QUARL)
Srivatsan Krishnan, Sharad Chitlangia, Maximilian Lam, Zishen Wan, Aleksandra Faust, Vijay Janapa Reddi : https://arxiv.org/abs/1910.01055
Code: https://github.com/harvard-edge/quarl
#DeepLearning #ReinforcementLearning #Quantization #Robotics
Srivatsan Krishnan, Sharad Chitlangia, Maximilian Lam, Zishen Wan, Aleksandra Faust, Vijay Janapa Reddi : https://arxiv.org/abs/1910.01055
Code: https://github.com/harvard-edge/quarl
#DeepLearning #ReinforcementLearning #Quantization #Robotics
arXiv.org
QuaRL: Quantization for Fast and Environmentally Sustainable...
Deep reinforcement learning continues to show tremendous potential in achieving task-level autonomy, however, its computational and energy demands remain prohibitively high. In this paper, we...
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
Yu et al.: https://arxiv.org/abs/1910.10897
#MachineLearning #ArtificialIntelligence #Robotics
Yu et al.: https://arxiv.org/abs/1910.10897
#MachineLearning #ArtificialIntelligence #Robotics
arXiv.org
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta...
Meta-reinforcement learning algorithms can enable robots to acquire new skills much more quickly, by leveraging prior experience to learn how to learn. However, much of the current research on...
Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning
Gupta et al.: https://arxiv.org/abs/1910.11956
Website : https://relay-policy-learning.github.io
#ReinforcementLearning #MachineLearning #Robotics
Gupta et al.: https://arxiv.org/abs/1910.11956
Website : https://relay-policy-learning.github.io
#ReinforcementLearning #MachineLearning #Robotics
arXiv.org
Relay Policy Learning: Solving Long-Horizon Tasks via Imitation...
We present relay policy learning, a method for imitation and reinforcement learning that can solve multi-stage, long-horizon robotic tasks. This general and universally-applicable, two-phase...
PyRoboLearn: A Python Framework for Robot Learning Practitioners
Delhaisse et al.: https://robotlearn.github.io/pyrobolearn/
#ArtificialIntelligence #Python #Robotics
Delhaisse et al.: https://robotlearn.github.io/pyrobolearn/
#ArtificialIntelligence #Python #Robotics
Dynamics-Aware Unsupervised Discovery of Skills
Sharma et al.: https://arxiv.org/abs/1907.01657
#MachineLearning #Robotics #ReinforcementLearning
Sharma et al.: https://arxiv.org/abs/1907.01657
#MachineLearning #Robotics #ReinforcementLearning
arXiv.org
Dynamics-Aware Unsupervised Discovery of Skills
Conventionally, model-based reinforcement learning (MBRL) aims to learn a global model for the dynamics of the environment. A good model can potentially enable planning algorithms to generate a...
Experience-Embedded Visual Foresight
Yen-Chen et al.: https://arxiv.org/abs/1911.05071
Demo: http://yenchenlin.me/evf/
#DeepLearning #MachineLearning #Robotics
Yen-Chen et al.: https://arxiv.org/abs/1911.05071
Demo: http://yenchenlin.me/evf/
#DeepLearning #MachineLearning #Robotics
arXiv.org
Experience-Embedded Visual Foresight
Visual foresight gives an agent a window into the future, which it can use to
anticipate events before they happen and plan strategic behavior. Although
impressive results have been achieved on...
anticipate events before they happen and plan strategic behavior. Although
impressive results have been achieved on...
Learning Keypoint Representations for Robot Manipulation
Yuke Zhu, IROS 2019 : http://ai.stanford.edu/~yukez/talks/keypoint_representations_for_interaction.pdf
#ArtificialIntelligence #DeepLearning #Robotics
Yuke Zhu, IROS 2019 : http://ai.stanford.edu/~yukez/talks/keypoint_representations_for_interaction.pdf
#ArtificialIntelligence #DeepLearning #Robotics
Challenges of Self-Supervision via Interaction in Robotics
Presentation by Julian Ibarz : https://bit.ly/2O0ZQZA
#ArtificialIntelligence #DeepLearning #Robotics
Presentation by Julian Ibarz : https://bit.ly/2O0ZQZA
#ArtificialIntelligence #DeepLearning #Robotics
Training Agents using Upside-Down Reinforcement Learning
Srivastava et al.: https://arxiv.org/abs/1912.02877
#MachineLearning #ArtificialIntelligence #Robotics
Srivastava et al.: https://arxiv.org/abs/1912.02877
#MachineLearning #ArtificialIntelligence #Robotics
Useful Models for Robot Learning
Slides by Marc Deisenroth : https://deisenroth.cc/talks/2019-12-14-neurips-ws.pdf
#ReinforcementLearning #Robotics #MetaLearning
Slides by Marc Deisenroth : https://deisenroth.cc/talks/2019-12-14-neurips-ws.pdf
#ReinforcementLearning #Robotics #MetaLearning
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
Engelcke et al.: https://arxiv.org/abs/1907.13052
#Artificialintelligence #DeepLearning #Robotics
Engelcke et al.: https://arxiv.org/abs/1907.13052
#Artificialintelligence #DeepLearning #Robotics
Robot development with Jupyter
Wolf Vollprecht : https://medium.com/@wolfv/robot-development-with-jupyter-ddae16d4e688
#Robotics #Jupyter #Python
Wolf Vollprecht : https://medium.com/@wolfv/robot-development-with-jupyter-ddae16d4e688
#Robotics #Jupyter #Python
Medium
Robot development with Jupyter
This post shows available tools to build browser based, advanced visualizations in Jupyter Notebooks for ROS and standalone web apps using
Deep Learning for 3D Point Clouds: A Survey
Guo et al.: https://arxiv.org/abs/1912.12033
#DeepLearning #MachineLearning #Robotics
Guo et al.: https://arxiv.org/abs/1912.12033
#DeepLearning #MachineLearning #Robotics
SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications
Hamdi et al.: http://arxiv.org/abs/1812.02132
Code http://github.com/ajhamdi/SADA
Video http://youtu.be/clguL24kVG0
#Cryptography #MachineLearning #Robotics
Hamdi et al.: http://arxiv.org/abs/1812.02132
Code http://github.com/ajhamdi/SADA
Video http://youtu.be/clguL24kVG0
#Cryptography #MachineLearning #Robotics
GitHub
ajhamdi/SADA
SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications - ajhamdi/SADA
CS 287 Advanced Robotics – Fundamental Knowledge
Abbeel et al.: https://people.eecs.berkeley.edu/~pabbeel/cs287-fa19/exam/cs287-fa19-exam-study-handout.pdf
#ArtificialIntelligence #ReinforcementLearning #Robotics
Abbeel et al.: https://people.eecs.berkeley.edu/~pabbeel/cs287-fa19/exam/cs287-fa19-exam-study-handout.pdf
#ArtificialIntelligence #ReinforcementLearning #Robotics
Introduction to Reinforcement Learning
By DeepMind: https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PLqYmG7hTraZDM- OYHWgPebj2MfCFzFObQ
#DeepLearning #ReinforcementLearning #Robotics
By DeepMind: https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PLqYmG7hTraZDM- OYHWgPebj2MfCFzFObQ
#DeepLearning #ReinforcementLearning #Robotics
YouTube
RL Course by David Silver - Lecture 1: Introduction to Reinforcement Learning
#Reinforcement Learning Course by David Silver# Lecture 1: Introduction to Reinforcement Learning
#Slides and more info about the course: http://goo.gl/vUiyjq
#Slides and more info about the course: http://goo.gl/vUiyjq