AI engineering glossary · Reinforcement learning
What is nash equilibrium?
Nash equilibrium: A situation in a multi-player game where no player can gain by changing only their own strategy while the others keep theirs. It is a standard notion of a stable outcome when several learners interact.
Nash equilibrium: an example
In rock-paper-scissors, everyone playing each move with probability 1/3 is the only equilibrium.
Related terms
More Reinforcement learning terms
- Natural policy gradient
- Noisy networks
- Off-policy
- Off-policy evaluation
- Offline reinforcement learning
- On-policy
- Optimal policy
- Options framework
Where you learn it
Nash equilibrium is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.