Near-Optimal Representation Learning for Hierarchical Reinforcement Learning
Author(s): Sherwin Chen Originally published on Towards AI. Beyond Hierarchical Reinforcement learning with Off-policy correction(HIRO) This is the second post of the series, in which we will talk about a novel Hierarchical Reinforcement Learning built upon HIerarchical Reinforcement learning with Off-policy correction(HIRO) …
EMI: Exploration with Mutual Information
Author(s): Sherwin Chen Originally published on Towards AI. A novel exploration method based on representation learning Source: Photo by Andrew Neel on Unsplash Reinforcement learning could be hard when the reward signal is sparse. In these scenarios, exploration strategy becomes essentially important: …
LLMs Encode Clinical Knowledge: A Quick Review
Author(s): Ronny Polle Originally published on Towards AI. Outline Introduction Contributions Limitations Conclusion References Introduction In the field of medicine, language is an enabler of key interactions for and between clinicians, researchers, and patients. This provides opportunities for leveraging LLMs for modeling …
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