Thesis: Rule-Based Interactive Assisted Reinforcement Learning
Reinforcement Learning (RL) has seen increasing interest over the past few years, partially owing to breakthroughs in the digestion and application of external information. The use of external information results in improved learning speeds and solutions to more complex domains. This thesis, a collection of five key contributions, demonstrates that comparable performance gains to existing … Continue reading Thesis: Rule-Based Interactive Assisted Reinforcement Learning
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