Reinforcement Learning in Continuous Spaces with Interactively Acquired Knowledge-based Models
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Completed
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The purpose of this project is to investigate the application of classical Artificial Intelligence (AI) techniques to the problem of Reinforcement Learning (RL) in continuous state/action spaces. This project is funded by the Wallenberg Autonomous Systems Program for Artificial Intelligence (WASP-AI).