AI engineering glossary · Reinforcement learning
What is count-based exploration?
Count-based exploration: An exploration approach that gives a bonus that decreases with how many times a situation has been visited, for example beta / sqrt(N(s)). Rarely visited situations look attractive, driving coverage of the world.
Count-based exploration: an example
A state visited 4 times gets bonus 0.1/2 = 0.05; one visited 100 times gets 0.01.
Related terms
More Reinforcement learning terms
- Credit assignment
- Curiosity-driven exploration
- DAgger
- Deadly triad
- Deep deterministic policy gradient
- Deep Q-network
- Deterministic policy
- Deterministic policy gradient
Where you learn it
Count-based exploration is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.