AI engineering glossary · Reinforcement learning
What is episode?
Episode: One complete run of interaction from a starting situation until a stopping condition, such as a win, a loss, a crash or a time limit. Learning is often organised as many such runs, with the total score of each run used as a measure of progress.
Episode: an example
One game of Ludo from the first dice roll to the last token reaching home is one episode; a training run may use 100,000 of them.
Related terms
More Reinforcement learning terms
- Episodic task
- Epsilon-greedy
- Experience replay
- Exploitation
- Exploration
- Exploration-exploitation trade-off
- Function approximation
- Goal-conditioned reinforcement learning
Where you learn it
Episode is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.