Reinforcement Learning

Exciting New Directions in ML/AI

Over the last few years, there have been several breakthroughs and exciting new research directions in Reinforcement Learning, Hippocampus Inspired Architectures, Attention and Few-Shot Learning. There has been a move towards multi-component, heterogeneous, stateful architectures, many guided by ideas from cognitive sciences. Google DeepMind and Google Brain are leading the… Read More »Exciting New Directions in ML/AI

Reading list – October 2017

This month’s reading list has two parts: a non-Reinforcement Learning list, and a Reinforcement Learning list. Since our next blog post will be on Reinforcement Learning, readers might like to refer to our RL reading list separately. Non-Reinforcement Learning reading list A Framework for searching for General Artificial Intelligence Authors:… Read More »Reading list – October 2017

Literature Review: ‘A Distributional Perspective on Reinforcement Learning’

This article assesses the research paper, ‘A Distributional Perspective on Reinforcement Learning’ by the authors, Marc G. Bellemare, Will Dabney and Remi Munos, published in the proceedings of the 34th International Conference on Machine Learning (ICML) in 2017. Bellemare et al.’s paper will be assessed on several criteria. Firstly, content… Read More »Literature Review: ‘A Distributional Perspective on Reinforcement Learning’

SDR-RL (Sparse, Distributed Representation with Reinforcement Learning)

Erik Laukien is back with a demo of Sparse, Distributed Representation with Reinforcement Learning. This topic is of intense interest to us, although the problem is quite a simple one. SDRs are a natural fit with Reinforcement Learning because bits jointly represent a state. If you associate each bit-pattern with… Read More »SDR-RL (Sparse, Distributed Representation with Reinforcement Learning)

Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function

This post is about a fantastic new paper by Michael R. Ferrier, titled:   Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function   The paper was posted to the NUPIC mailing list and can be found via:   http://numenta.org/community-content.html   The paper itself… Read More »Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function

Recent HTM projects

It’s exciting to see growing interest and participation in the AGI community. This is another brief post to share two examples. In this case, they both build on one approach to AGI, and that is HTM. FXAI – Explorations Into Computational Intelligence A blog that is pretty well described by… Read More »Recent HTM projects

Introduction

by David Rawlinson and Gideon Kowadlo   The Blog This blog will be written by several people. Other contributors are welcome – send us an email to introduce yourself! The content will be a series of short articles about a set of common architectures for artificial general intelligence (AGI). Specifically,… Read More »Introduction