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A Bayesian Perspective on Q-Learning
Can we use Q-value distributions to efficiently explore the state-action space?
bayes-rule q-learning interactive bayesian-deep-learning
Machine Learning Methods Explained (+ Examples)
Most common techniques used in data science projects; get to know them through easy-to-understand examples and put them into practice in your own ML ...
machine-learning deep-learning unsupervised-learning dimensionality-reduction
Building AI Trading Systems
Lessons learned building a profitable algorithmic trading system using Reinforcement Learning techniques.
trading finance machine-learning algorithmic-trading
Rlx: A modular Deep RL library for research
"rlx" is a Deep RL library written on top of PyTorch & built for educational and research purpose.
reinforcement-learning deep-learning article code
NetHack Learning Environment (NLE)
A procedurally-generated grid-world dungeon-crawl game that strikes a great balance between complexity and speed for single-agent RL research.
reinforcement-learning game nethack gym
Plan2Explore: Plan to Explore via Self-Supervised World Models
A self-supervised reinforcement learning agent that tackles task-specific and the sample efficiency challenges.
self-supervised-learning reinforcement-learning plan2explore article
Reinforcement learning is supervised learning on optimized data
In this blog post we discuss a mental model for RL, based on the idea that RL can be viewed as doing supervised learning on the “good data”.
reinforcement-learning supervised-learning optimization dynamic-programming
Deep Reinforcement Learning Amidst Lifelong Non-Stationarity
How can robots learn in changing, open-world environments? We introduce dynamic-parameter MDPs, to capture environments with persistent, unobserved ...
reinforcement-learning non-stationarity off-policy markov-decision-process
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