Robot Learning

Eureka

Eureka is a 2023 NVIDIA method that uses a large language model, originally GPT-4, to automatically write and evolve reward functions for reinforcement learning. Given a task description and the simulation environment's source code, the LLM generates candidate reward code, receives training statistics as feedback, and iteratively refines its proposals. Eureka-designed rewards outperformed human-engineered ones on most benchmark tasks and enabled simulated dexterous pen spinning.

Why it matters for physical AI

Reward engineering is a chief bottleneck of applied reinforcement learning, and code-writing language models turn it into an automated search, foreshadowing self-improving skill acquisition pipelines.