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Found 3 papers, 1 papers with code
Closing the Gap between TD Learning and Supervised Learning -- A Generalisation Point of View
Based on this analysis, we construct new datasets to explicitly test for this property, revealing that SL-based methods lack this stitching property and hence fail to perform combinatorial generalization.
Searching for High-Value Molecules Using Reinforcement Learning and Transformers
Reinforcement learning (RL) over text representations can be effective for finding high-value policies that can search over graphs.
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective
In this work, we propose a single objective which jointly optimizes a latent-space model and policy to achieve high returns while remaining self-consistent.
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