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Talk Interactive and Incremental Robot Learning by Dongheui Lee
Robot-Use Agents: Why General-Purpose Models May Win in Robotics
Robot Learning: Learning Reward Models and Using Foundational Models for Rewards
Interactively Learning the Dynamics of Articulated Objects
LEGO Robot Art! Learn Functions & Parameters Through Coding
Lecture 54: Machine Learning for Robot Arms
Learning task controllers on a humanoid robot using multi-objective optimization (Talos robot)
Perceptual Robot Learning (David Held, CMU)
Learning User-Preferred Mappings for Intuitive Robot Control
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Last Updated: September 27, 2026
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Anca Dragan, UC Berkeley simons.berkeley.edu/talks/anca-dragan-02-13-2017 Anca Dragan (UC Berkeley) simons.berkeley.edu/talks/tbd-182 Theory of Reinforcement paper: proceedings.mlr.press/v78/bajcsy17a/bajcsy17a.pdf blog post: bair.berkeley.edu/blog/2018/02/06/phri/ lab ... One of the biggest surprises in AI over the last few years has been how well coding agents generalize beyond software. I (Glen Berseth) discuss reward Designing controllers for complex paper: arxiv.org/abs/2007.11627 abstract: When humans control drones, cars, and Many recent foundational model papers use What are the properties of a model that translates image-based
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