Summary: In the first part of this series we described the basics of Reinforcement Learning (RL). In this article we describe how deep learning is augmenting RL and a variety of challenges and considerations that need to be addressed in each implementation.
Added by William Vorhies on August 29, 2017 at 9:03am — No Comments
Summary: Reinforcement Learning (RL) is likely to be the next big push in artificial intelligence. It’s the core technique for robotics, smart IoT, game play, and many other emerging areas. But the concept of modeling in RL is very different from our statistical techniques and deep learning. In this two part series we’ll take a look at the basics of RL models, how they’re built and used. In the next part, we’ll address some of the complexities that make development a…Continue
Added by William Vorhies on August 22, 2017 at 9:00am — No Comments
"Measurement owes its existence to Earth; estimation of quantity to measurement; calculation to estimation of quantity; balancing of chances to calculation; and victory to balancing of chances." - Sun Tzu, The Art of War (Translated by L. Giles)
The quote from Sun Tzu seems to suggest how a military leader gathers data; adapts to different situations; and makes decisions weighing the circumstances. It says that the balancing of chances depends on "calculation." I…Continue
Given the nature of the community, presumably many visitors already have a strong understanding of the nature of quantitative data. Perhaps more mysterious is the idea of qualitative data especially since it can sometimes be expressed in quantitative terms. For instance, "stress" as an internal response to an externality differs from person to person; yet it would be possible to canvas a large number of people and express stress levels as an aggregate based on a perceptual gradient: minimal,…Continue
Added by Don Philip Faithful on October 25, 2014 at 6:37am — No Comments