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reinforcement-learning

What is the example of a continous state space and continous action space in Reinforcement learning with mathematical notation?

how are they represented in mathematical notation ?

Solution

  • Discrete state space -> where states can have finite value. for eg If there are only 3 types of weather: sunny, foggy, or rainy then this is analogous to a state-space that takes on three discrete values

    Continous state space -> where states can have infinite value For example, for a car, we might represent the state as (x,y,θ, x,˙ y,˙ ˙θ), comprising its position (x,y); orientation θ; velocity in the x and y directions x˙ and ˙y; and angular velocity ˙θ.

    Hence, S = R^6, is an infinite set of states, because there is an infinite number of possible positions and orientations for the car