3 papers
cs.AI2024
Enhancing Analogical Reasoning in the Abstraction and Reasoning Corpus via Model-Based RL
Jihwan Lee, Woochang Sim, Sejin Kim +1
This paper demonstrates that model-based reinforcement learning (model-based RL) is a suitable approach for the task of analogical reasoning. We hypothesize that model-based RL can…
cs.LG2024
Narrowing the Focus: Learned Optimizers for Pretrained Models
Gus Kristiansen, Mark Sandler, Andrey Zhmoginov +4
In modern deep learning, the models are learned by applying gradient updates using an optimizer, which transforms the updates based on various statistics. Optimizers are often hand…
cs.AI2024
ARCLE: The Abstraction and Reasoning Corpus Learning Environment for Reinforcement Learning
Hosung Lee, Sejin Kim, Seungpil Lee +4
This paper introduces ARCLE, an environment designed to facilitate reinforcement learning research on the Abstraction and Reasoning Corpus (ARC). Addressing this inductive reasonin…