Neuro-evolutionary Frameworks for Generalized Learning Agents

4 Feb 2020 Thommen George Karimpanal

The recent successes of deep learning and deep reinforcement learning have firmly established their statuses as state-of-the-art artificial learning techniques. However, longstanding drawbacks of these approaches, such as their poor sample efficiencies and limited generalization capabilities point to a need for re-thinking the way such systems are designed and deployed... (read more)

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