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Safer Exploration in Deep Reinforcement Learning using Action Priors with Sicelukwanda Zwane - TWiML Talk #235

Safer Exploration in Deep Reinforcement Learning using Action Priors with Sicelukwanda Zwane - TWiML Talk #235

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)


Safer Exploration in Deep Reinforcement Learning using Action Priors with Sicelukwanda Zwane - TWiML Talk #235

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

ratings:
Length:
54 minutes
Released:
Mar 1, 2019
Format:
Podcast episode

Description

Today we conclude our Black in AI series with Sicelukwanda Zwane, a masters student at the University of Witwatersrand and graduate research assistant at the CSIR. At the workshop, he presented on “Safer Exploration in Deep Reinforcement Learning using Action Priors,” which explores transferring action priors between robotic tasks to reduce the exploration space in reinforcement learning, which in turn reduces sample complexity. In our conversation, we discuss what “safer exploration” means in this sense, the difference between this work and other techniques like imitation learning, and how this fits in with the goal of “lifelong learning.” The complete show notes for this episode can be found at https://twimlai.com/talk/235. To follow along with the Black in AI series, visit https://twimlai.com/blackinai19.
Released:
Mar 1, 2019
Format:
Podcast episode

Titles in the series (100)

This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders. These creators, builders, makers and influencers value TWiML as an authentic, trusted and insightful guide to all that’s interesting and important in the world of machine learning and AI. Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.