Microsoft Is Going Big On Reinforcement Learning. Here’s How

From recommendations to gaming, Microsoft has been using popular techniques like reinforcement learning to create efficient products.

When it comes to research in new-age technologies, Microsoft has been striving hard to stay ahead of its competitors. From recommendations to gaming, the tech giant has been using popular techniques like reinforcement learning to create efficient products for customers that match their interests.

The foundational work in reinforcement learning (RL) started back in 1992, in which the researchers worked on Simple Statistical Gradient. This year, the tech giant has made significant contributions in the ongoing AI conference known as NeurIPS 2020. The three key research areas that are being focussed this year include batch reinforcement learning; a strategic exploration that has given rich observations; and representation learning.

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The Association of Data Scientists is holding a full-day workshop on building games using reinforcement learning on Saturday, February 20.

Gentle explanation and implementation of SARSA and Q-learning in the context of CartPole game. Intro to Reinforcement Learning: Temporal Difference Learning, SARSA Vs. Q-learning

Towards building an artificial brain. The ELI5 definition for Reinforcement Learning would be training a model to perform better by iteratively learning from its previous mistakes.

Dummies guide to Reinforcement learning, Q learning, Bellman Equation. You’re getting bore stuck in lockdown, you decided to play computer games to pass your time.

Paper Summary: Discovering Reinforcement Learning Agents. Learning the Update Rule through Meta-Learning. One exception to this rule can be found in the field of meta-learning.