Facebook Open Sources ELF OpenGo

May 3, 2018

Table of Contents

Inspired by DeepMind’s work, we kicked off an effort earlier this year to reproduce their recent AlphaGoZero results using FAIR’s Extensible, Lightweight Framework (ELF) for reinforcement learning research. The goal was to create an open source implementation of a system that would teach itself how to play Go at the level of a professional human player or better. By releasing our code and models we hoped to inspire others to think about new applications and research directions for this technology.

Source: fb.com

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TDM: From Model-Free to Model-Based Deep Reinforcement Learning

While simple, this thought experiment highlights some important aspects of human intelligence. For some tasks, we use a trial-and-error approach, and for others we use a planning approach. A similar phenomena seems to have emerged in reinforcement learning (RL).

Introduction to Decision Tree Learning

From Kaggle to classrooms, one of the first lessons in machine learning involves decision trees. The reason for the focus on decision trees is that they aren’t very mathematics heavy compared to other ML approaches, and at the same time, they provide reasonable accuracy on classification problems.

Facebook Open Sources ELF OpenGo

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