Karol Hausman
3 أوراق في مجموعة PaperMetrix
أوراق هذا المؤلف
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A Geometric Perspective on Self-Supervised Policy Adaptation
2020 · arXiv (Cornell University)
One of the most challenging aspects of real-world reinforcement learning (RL) is the multitude of unpredictable and ever-changing distractions that could divert an agent from what was tasked to do in its training environment. While …
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Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
2022 · arXiv (Cornell University)
Large language models can encode a wealth of semantic knowledge about the world. Such knowledge could be extremely useful to robots aiming to act upon high-level, temporally extended instructions expressed in natural language. However, a …
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Inner Monologue: Embodied Reasoning through Planning with Language Models
2022 · arXiv (Cornell University)
Recent works have shown how the reasoning capabilities of Large Language Models (LLMs) can be applied to domains beyond natural language processing, such as planning and interaction for robots. These embodied problems require an agent …