Leslie Kaelbling: Reinforcement Learning, Planning, and Robotics | Lex Fridman Podcast #15

ℹ️ EPISODE INFO

Released

March 12, 2019

Duration

1h 1m

Channel

Lex Fridman Podcast

Watch on YouTube

▶ Open ↗

🎤 SPEAKERS

• Lex Fridman

  host

• Leslie Kaelbling

  guest

• Narrator

  other

🧾 EPISODE SUMMARY

In this episode of Lex Fridman Podcast, featuring Lex Fridman and Leslie Kaelbling, Leslie Kaelbling: Reinforcement Learning, Planning, and Robotics | Lex Fridman Podcast #15 explores leslie Kaelbling on uncertainty, abstraction, and truly intelligent robots Leslie Kaelbling discusses her path from philosophy to AI and robotics, arguing that logic, formal semantics, and materialism naturally underpin her view that human-level robot behavior is a purely technical challenge. She traces the cyclical history of AI, contrasting expert systems, symbolic reasoning, and modern learning-based approaches, emphasizing the central role of abstraction, uncertainty, and hierarchical planning. A major theme is planning and acting under partial observability via POMDPs and belief-space planning, and how robots must reason about both the world and their own uncertainty. She also critiques current research culture and publishing, champions open access and deeper theory, and stresses the need to design good objectives and structural biases rather than rely on monolithic end-to-end learning.

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