Reinforcement learning is one of the most intriguing fields in machine learning, and has recently made tremendous breakthroughs in a variety of domains, but perhaps most notably in un-assisted game play. In this talk, we’ll take a look at how to use the miner package to train learning agents in Minecraft using R bindings for CNTK, Keras and Tensorflow. We’ll start with simple tasks, such as learning how to ascend mountains and stairs, to more challenging tasks such as solving random mazes with obstacles using deep Q-learning. The talk will provide examples using the new R bindings for CNTK, as well as the Keras and Tensorflow packages, and describe how to use docker images for Minecraft and CUDA enabled containers with R to easily and affordably try out the examples on cloud platforms.

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