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Reinforcement Learning for Fun
How to apply reinforcement learning to play games and have fun.
Author: Rodolfo Mendes
Residual Reinforcement Learning
TabbieMath :: Reinforcing your learning.
PLE: A Reinforcement Learning Environment — PyGame Learning Environment 0.1.dev1 documentation
d3rlpy - An offline deep reinforcement learning library. — d3rlpy documentation
ChainerRL, a deep reinforcement learning library — ChainerRL 0.8.0 documentation
ReAgent: Applied Reinforcement Learning Platform — ReAgent 1.0 documentation
Welcome to Awesome Streamlit’s documentation! — Awesome Streamlit documentation
Welcome to Awesome Panel’s documentation! — Awesome Panel documentation
Reinforcement Learning for Games | Sharing my path to applying Reinforcement Learning to modern games.
Sharing my path to applying Reinforcement Learning to modern games.
Author: Opher Lieber
Unsupervised Reinforcement Learning (URL)
An ICML 2021 Workshop on Unsupervised Reinforcement Learning
Reinforcement Learning: Theory and Algorithms
University of Washington. Research interests: Machine Learning, Artificial Intelligence, Optimization, Statistics
Reinforcement Learning Türkiye — Website
TalkRL: The Reinforcement Learning Podcast
TalkRL podcast is All Reinforcement Learning, All the Time. In-depth interviews with brilliant people at the forefront of RL research and practice. Guests from places like MILA, MIT, DeepMind, Berkeley, Amii, Oxford, Google Research, Brown, Waymo, Caltech, and Vector Institute. Hosted by Robin Ranjit Singh Chauhan. Technical content.
Reinforcement-Learning zur dispositiven Auftragssteuerung
Innovativer Ansatz zur intelligenten Auftragssteuerung auf Basis von Reinforcement-Learning
Tensorforce: a TensorFlow library for applied reinforcement learning — Tensorforce 0.6.5 documentation
Some Awesome Minecraft - A Family Friendly Minecraft Server
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NeurIPS 2019 Optimization Foundations of Reinforcement Learning Workshop | Optimization Foundation of Reinforcement Learning
Workshop at NeurIPS 2019, Dec 14th, 2019
Demo Videos for Minecraft | Learn Minecraft Through Videos
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Contingency-Aware Exploration in Reinforcement Learning
Contingency-Aware Exploration in Reinforcement Learning (ICLR 2019)
Author: Choi; Guo; Moczulski et al
An Optimistic Perspective on Offline Reinforcement Learning
Aakash Maroti | Reinforcement Learning Researcher
Reinforcement Learning for Traffic Signal Control
AWRL -- Asian Workshop on Reinforcement Learning
Welcome to Minecraft Bedrock Launcher’s documentation!¶
reinforcement! | Reinforcement !
Stable-Baselines3 Docs - Reliable Reinforcement Learning Implementations — Stable Baselines3 1.2.1a1 documentation
Multi-Agent Reinforcement Learning | This blog contains articles on Reinforcement Learning and it’s applications to Multi-Agent Systems. Thi
This blog contains articles on Reinforcement Learning and it’s applications to Multi-Agent Systems. This is a part of the Multi-Agent Reinforcement Learning project taken up at IEEE-NITK.
Author: Multi-Agent Reinforcement Learning
Welcome to Awesome Django Timezones’s documentation! — Awesome Django Timezones 0.3.0 documentation
Welcome to django-awesome-snippets’s documentation! — django-awesome-snippets 0.2 documentation
Welcome to Extendable Minecraft Server Manager’s documentation! — Extendable Minecraft Server Manager 6.0.3b0 documentation
Samir – Interests in Robotics, Deep/Machine Learning, Reinforcement Learning
Interests in Robotics, Deep/Machine Learning, Reinforcement Learning
Welcome to Learning Notebook’s documentation! — Learning Notebook v1.0 documentation
Welcome to learning-python’s documentation! — learning-python 0.9 documentation
IRLD 2021: Israeli Reinforcement Learning day
TERESA | Telepresence Reinforcement-learning Social Agent
enliteAI - Reinforcement Learning, Computer Vision and AI Research
enliteAI is a technology provider for Artificial Intelligence. We are the maker of MazeRL, an open-source framework for applied Reinforcement Learning and Detekt, a modern geospatial data platform supporting the entire mobile mapping and asset management life cycle.
TensorForce-Client - Running Parallelized Reinforcement Learning Experiments in the Cloud — TensorForce-Client 0.1.0a5 documentation
Poke-env: A python interface for training Reinforcement Learning pokemon bots — Poke-env documentation
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Learn Awesomely
gurkin33 learning awesome things
База знаний от gurkin33. Сетевые технологии и не только.
Tebo.me - Make learning more awesome!
Tebo.me - Make learning more awesome!
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imbalanced-learn documentation¶
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The company has recently expanded its operations in the South East with the development of a new industry leading reinforcing rod fabrication plant in Rainham. The new 10 acre site has been developed at a cost of over £9m to provide state of the art cut and bent production space along with additional storage facilities [...]Read More...
Navneet Madhu Kumar - Deep Reinforcement Learning FTW
Writings about Deep Reinforcement Learning and Machine Learning.
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ICLR 2019 Task-Agnostic Reinforcement Learning Workshop
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mcsquared – Let our AI guide you with reinforcement learning
MC.Seacraft.co. A factions Minecraft server with awesome free kits.
Deep Learning with Tensorflow Documentation — Deep-Learning-TensorFlow latest documentation
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scikit-learn-extra documentation — scikit-learn-extra 0.2.0 documentation
CSC2541-F18 Topics in Machine Learning - Deep Reinforcement Learning (Fall 2018)
CSC2541-F18 course website
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Viva English – Awesome learning site
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All about reinforced concrete structures for constructors
Reinforcing Steel | Brisbane | Pacreo Reinforcing
Your Trusted Reinforcing Supplier. PACREO REINFORCING. Pacreo has been supplying Reinforcing & Concrete Products for over 15 years.
Elasticsearch Learning to Rank: the documentation¶
Learn More — trakt.py 4.4.0 documentation
AB and Me | learn, document, remember
Adam, Blake and Me. Expat living|Travels|Life in General
Author: Alvin; AB; Me
Neuroscience, machine learning, reinforcement learning, robotics, brain-computer interfaces – Ilya Kuzovkin
Have a look at the latests posts below, pick a topic in the menu above, and, I hope, you’ll find something of interest!
Author: Ilya Kuzovkin
RLDM | The Multi-disciplinary Conference on Reinforcement Learning and Decision Making
Author: Ross Otto
Deep Reinforcement Learning and Control Spring 2017, CMU 10703
Pwnagotchi - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.
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