Decisions from Data: How Offline Reinforcement Learning Will Change How We Use ML

·Sergey Levine··

A ride sharing company collects a dataset of pricing and discount decisions with corresponding changes in customer and driver behavior, in order to optimize a dynamic pricing strategy. An online vendor records orders and inventory levels to generate an inventory level management policy. An autonomous car company records driving data from human drivers to train an improved end-to-end vision-based driving controller.All of these applications have two things in common: we would consider each of the...

Read full article →

Related Articles

OpenAI’s o1 correctly diagnosed 67% of ER patients vs. 50-55% by triage doctors
donsupreme · Hacker News · 18d ago
Accelerating Gemma 4: faster inference with multi-token prediction drafters
amrrs · Hacker News · 15d ago
A couple million lines of Haskell: Production engineering at Mercury
unignorant · Hacker News · 18d ago
Using “underdrawings” for accurate text and numbers
samcollins · Hacker News · 19d ago
ProgramBench: Can language models rebuild programs from scratch?
jonbaer · Hacker News · 14d ago