►CS4973/  6984:   Programming with Probabilities
▼Notes
►2 Probabilistic Programming
On this page:
2.1 Basic Modeling in Roulette
2.2 The Probability Word Problem
2.3 A Formal Language for Probability
2.4 Design Recipe
References
9.1
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2 Probabilistic Programming🔗

 #lang roulette/example/disrupt package: roulette

Given the omnipresent nature of probability and its centrality to science, programming, and countless other endeavors, it is only natural that it has found its way into our programming languages. Such programming languages are called probabilistic programming language: these are programming languages that denote probability distributions.

> (flip 0.5)

┌─────┬───────────┐

│Value│Probability│

├─────┼───────────┤

│#t   │0.5        │

│#f   │0.5        │

└─────┴───────────┘

2.1 Basic Modeling in Roulette🔗

2.2 The Probability Word Problem🔗

2.3 A Formal Language for Probability🔗

These foundational rules of probability are due to  (Kolmogorov 2018).

Let’s take a moment to be more mathematically rigorous about our definitions of probability so that we can all be on the same page. Formally, let \Omega be a finite set called the sample space. The sample space is the set of all observable outcomes

You likely had prior experiences in other classes where you worked with probability, and you were given questions like

2.4 Design Recipe🔗

References🔗

Andrei Nikolaevich Kolmogorov. Foundations of the theory of probability: Second English Edition. Courier Dover Publications, 2018.

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