Relational, Object-Centric Agents for Completing Simulated Household Tasks with Wilka Carvalho - #402
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) - Un pódcast de Sam Charrington
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Today we’re joined by Wilka Carvalho, a PhD student at the University of Michigan, Ann Arbor. In our conversation, we focus on his paper ‘ROMA: A Relational, Object-Model Learning Agent for Sample-Efficient Reinforcement Learning.’ In the paper, Wilka explores the challenge of object interaction tasks, focusing on every day, in-home functions. We discuss how he’s addressing the challenge of ‘object-interaction’ tasks, the biggest obstacles he’s run into along the way.
