1 research outputs found
Performing Deep Recurrent Double Q-Learning for Atari Games
Currently, many applications in Machine Learning are based on define new
models to extract more information about data, In this case Deep Reinforcement
Learning with the most common application in video games like Atari, Mario, and
others causes an impact in how to computers can learning by himself with only
information called rewards obtained from any action. There is a lot of
algorithms modeled and implemented based on Deep Recurrent Q-Learning proposed
by DeepMind used in AlphaZero and Go. In this document, We proposed Deep
Recurrent Double Q-Learning that is an implementation of Deep Reinforcement
Learning using Double Q-Learning algorithms and Recurrent Networks like LSTM
and DRQN.Comment: Accepted paper on LatinXinAI Workshop co-located with the
International Conference on Machine Learning (ICML) 201