On March 4, I was contacted by the Xinhua News Agency to comment on the upcoming Go match between Google DeepMind’s AlphaGo algorithm and the top-Go player Lee Sedol. I am posting the questions and answers below:
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Posts Tagged ‘Deep Learning’
AlphaGo vs Lee Sedol – The new AI Challenge
Posted: 2016-03-12 in researchTags: Deep Learning, Reinforcement Learning
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NIPS 2015 – Deep RL Workshop
Posted: 2015-12-13 in conferences, researchTags: Deep Learning, Reinforcement Learning
This is a brief summary of the first part of the Deep RL workshop at NIPS 2015. I couldn’t get a seat for the second half…
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
Posted: 2015-07-23 in paper of the day, researchTags: Control, Deep Learning, Dynamical System, Reinforcement Learning, Variational Inference
Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin Riedmiller:
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
arXiv, 2015
This paper deals with the problem of model-based reinforcement learning (RL) from images. The idea behind model-based RL is to learn a model of the transition dynamics of the system/robot and use this model as a surrogate simulator. This is helpful if we want to minimize experiments with a (physical/mechanical) system. The added difficulty addressed in this paper is that this predictive transition model should be learned from raw images where only pixel information is available.
