AI engineering glossary · Reinforcement learning
What is transition probability?
Transition probability (also called Transition function, Dynamics): The probability of landing in each possible next situation after making a given choice in a given situation. Written P(s' given s, a). Together with the score function, it fully describes how the surroundings behave in a formal model.
Transition probability: an example
If a robot on a wet floor tries to move right, P(right square) = 0.8, P(stay) = 0.1, P(slip down) = 0.1.
Related terms
More Reinforcement learning terms
- Twin delayed DDPG
- Upper confidence bound
- Value iteration
- World model
- A3C
- Action-value function
- Actor-critic
- Agent
Where you learn it
Transition probability is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.