#TWIMLfest: Office Hours – Reinforcement Learning

In the Office Hours series, we invite experts and practitioners in various topic areas for AMA (ask-me-anything) style sessions to answer community member questions. The intent is to answer technical questions and/or help participants advance their specific projects and interests. This week’s topic will be centered on Reinforcement Learning!

Resources:

Show notebooks in Drive – https://colab.research.google.com/github/psc-g/intro_to_rl/blob/master/Introduction_to_reinforcement_learning.ipynb
Streamlit – https://www.streamlit.io/
#302 – Deep Reinforcement Learning for Logistics at Instadeep w/ Karim Beguir – https://twimlai.com/twiml-talk-302-deep-reinforcement-learning-for-logistics-at-instadeep-with-karim-beguir/
Project Bonsai – https://azure.microsoft.com/en-us/services/project-bonsai/#features
David Silver lectures – https://www.davidsilver.uk/teaching/
Reinforcement Learning: An Introduction by Richard Sutton https://web.stanford.edu/class/psych209/Readings/SuttonBartoIPRLBook2ndEd.pdf
Theoretical Computational NeuroScience by Peter Dayan – http://www.gatsby.ucl.ac.uk/~lmate/biblio/dayanabbott.pdf
Agence – https://www.agence.ai/
Emma Brunskill – https://cs.stanford.edu/people/ebrun/
Unity Machine Learning Agents – https://unity.com/products/machine-learning-agents
Unity Machine Learning Agents GitHub – https://github.com/Unity-Technologies/ml-agents
Invariant Causal Prediction for Block MDPs – https://arxiv.org/abs/2003.06016
Causal Modeling in Machine Learning by Robert O. Ness – https://github.com/robertness/causalML/blob/master/syllabus_NEU.md
Doubly Robust Off-policy Value Evaluation for Reinforcement Learning – https://arxiv.org/abs/1511.03722
Gridworld Playground – http://gridworld-playground.glitch.me/
Join the TWIML Slack – https://twimlai.com/community
Sim2Real – http://www.andrew.cmu.edu/course/10-703/slides/Lecture_sim2realmaxentRL.pdf
Duckietown – https://www.duckietown.org/
AI Research at JP Morgan Chase with Manuela Veloso – #371 – https://twimlai.com/twiml-talk-371-ai-research-at-jp-morgan-chase-with-manuela-veloso/
Privacy-Preserving Decentralized Data Science with Andrew Trask – Talk #241 – https://twimlai.com/twiml-talk-241-privacy-preserving-decentralized-data-science/
Secure and Private Deep Learning with PySyft – Democast #4 – https://twimlai.com/secure-and-private-deep-learning-with-pysyft-democast-4/
Multi-agent RL theory survey – https://arxiv.org/abs/1911.10635
CoPO – https://sites.google.com/view/you-rl-copo
Advances in Reinforcement Learning with Sergey Levine – #355 – https://twimlai.com/twiml-talk-355-advancements-in-reinforcement-learning-with-sergey-levine/
Workshop on Automated Algorithm Design – http://www.cs.cmu.edu/~ckingsf/AutoAlg2019/
Simons Workshop – https://simons.berkeley.edu/workshops/schedule/14238
Regret Bounds for the Adaptive Control of Linear Quadratic Systems – http://proceedings.mlr.press/v19/abbasi-yadkori11a/abbasi-yadkori11a.pdf
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems – https://arxiv.org/pdf/2003.11227.pdf
Adaptive Control and Regret Minimization in Linear Quadratic Gaussian (LQG) Setting – https://arxiv.org/pdf/2003.05999.pdf
Regret Minimization in Partially Observable Linear Quadratic Control – https://arxiv.org/pdf/2002.00082.pdf

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