Robotics and Learning
Chelsea expresses a desire for broader engagement with robotics, acknowledging that many may feel intimidated by the practical challenges. She highlights the potential of simulated environments for studying control agents and emphasizes the readiness of algorithms for tackling complex tasks, including multitask and hierarchical reinforcement learning. As advancements continue, significant progress in deep reinforcement learning within challenging settings is anticipated.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Trends in Reinforcement Learning with Chelsea Finn - #335
Related Questions
Is the interaction of robots in the physical world a signal that could be used in reinforcement learning, as discussed in the episode Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10 and the clip Robot Psychology?
Is the interaction of robots in the physical world a signal that could be used in reinforcement learning as discussed in the episode Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10 and the clip Robot Psychology?
So as we have robots interact in the physical world, is that a signal that could be used in reinforcement learning in the context of the episode Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10 and the clip Robot Psychology?