Deep Reinforcement Learning as Foundation for Artificial General Intelligence

Part of the Atlantis Thinking Machines book series (ATLANTISTM, volume 4)


Deep machine learning and reinforcement learning are two complementing fields within the study of intelligent systems. When combined, it is argued that they offer a promising path for achieving artificial general intelligence (AGI). This chapter outlines the concepts facilitating such merger of technologies and motivates a framework for building scalable intelligent machines. The prospect of utilizing custom neuromorphic devices to realize large-scale deep learning architectures is discussed, paving the way for achieving human level AGI.


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Authors and Affiliations

  1. 1.Machine Intelligence Lab, Department of Electrical Engineering and Computer ScienceUniversity of TennesseeChattanoogaUSA

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