Deep Reinforcement Learning Gets Boost with Dopamine, but Still Requires a Technology Paradigm Shift.

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4Q 2018 | IN-5291


What Is Deep Reinforcement Learning and Why Does It Matter?


Deep Reinforcement Learning (RL) is a technique used by data scientists working in AI. It is an algorithm that can learn to develop solutions over multiple steps to achieve a goal independently from human intervention. The critical challenge for software developers building deep-RL algorithms is to set the goals and reward functions that then inform the learning process. Deep RL has been given top billing as a potential AI technology that could enable far greater autonomation in the automotive, consumer, financial, and industrial spaces.

The field has seen a number of significant advances in the past few years. These advances have allowed deep-RL software agents to play games at superhuman levels. Notable projects in reinforcement learning have included DeepMind’s Deep Q Networks (DQN) (a software that could play Atari games), AlphaGo and AlphaGo Zero (a DeepMind software that became the world’s best player of the board game Go), and OpenAI’s Five which learned to play the video game Dota2. Deep RL has also now seen its…

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