AI engineering glossary · Reinforcement learning
What is self-play?
Self-play: A training approach in which a learner improves by playing against copies or earlier versions of itself, creating an automatic curriculum of ever stronger opponents. It powered top game-playing systems.
Self-play: an example
A Go program plays millions of games against itself, learning from wins and losses.
Related terms
More Reinforcement learning terms
- Sim-to-real transfer
- Softmax exploration
- Sparse reward
- State
- Stochastic policy
- Target network
- TD error
- TD(0)
Where you learn it
Self-play is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.