Google releases AI based open source reinforcement learning framework
Google is now helping its researchers team to train the Artificial Intelligence models with the help of an open sourcing a reinforcement learning frameworks which are mainly used for its projects.
Reinforcement learning has been used for some of the most impressive Artificial Intelligence demonstrations so far which also includes those which beat the human professional games at the Dota 2 and Alpha Go. Google Subsidiary DeepMind also uses it for the Deep Q Network(DQN).
With the help of building a reinforcement learning framework talks both the significant time and resources. For AI, to reach its full level of full potential, it needs to be much more easily accessible.
Now, Google has made an open source reinforcement framework which is based on TensorFlow, available on the GitHub. Pablo Samuel Castro and Marc G. Bellemare, Google Brain researchers, wrote in a blog post:
“Inspired by one of the main components in reward-motivated behavior in the brain and reflecting the strong historical connection between neuroscience and reinforcement learning research, this platform aims to enable the kind of speculative research that can drive radical discoveries.
This new release also consists of a set of collaboration which clarifies how to use the open source framework. Google framework has been designed with three new focuses” stability, flexibility, and productivity.
The company is also providing the 15 code examples for the Arcade learning Environment, a platform which uses the video games that helps to evaluate the performance of the Artificial Intelligence technology along with the help of a four machine learning concept: Implicit Quantile Network, Rainbow agent, c51 and the aforementioned DQN.
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