AI engineering glossary · Reinforcement learning
What is sample efficiency?
Sample efficiency: How much learning is achieved per unit of interaction data. A sample-efficient method reaches good performance with few real steps. It matters when each step is slow, costly or risky, as with physical robots.
Sample efficiency: an example
One method needs 10 million game frames to reach a score; another reaches it with 100,000, so it is 100 times more sample efficient.
Related terms
More Reinforcement learning terms
- SARSA
- Score function estimator
- Self-play
- Sim-to-real transfer
- Softmax exploration
- Sparse reward
- State
- Stochastic policy
Where you learn it
Sample efficiency is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.