Intro Chapter 1: The Core Language Chapter 2: Forward Models Chapter 3: Conditioning Chapter 4: Inference Algorithms

Introduction: References of the Course

This webpage is used in the course of LANGUAGES AND ALGORITHMS FOR ARTIFICIAL INTELLIGENCE, Modulo 4, given in the University of Bologna in 2023. Several examples given during the course are written and can be run using the webPPL langage.

References for webPPL

This course and this webpage on Probabilistic Programming, based on WebPPL, is inspired by the book N. D. Goodman, J. B. Tenenbaum, and The ProbMods Contributors (2016). Probabilistic Models of Cognition (2nd ed.). From this site

You can refer to the documentation, and the main page.

Advanced topics using webPPL and examples can be found also in the book from N. D. Goodman and A. Stuhlmüller (electronic). The Design and Implementation of Probabilistic Programming Languages. From this site.

References for Church

Before being a langage based on JS, webPPL was initially a langage based on Scheme, called Church. Some old references for Church are still relevant for webPPL, even if the core syntax changed.

I recommend the course on Church available on the MIT OpenCourseWare Youtube Channel: First Part / Second Part

And some examples written in Church

Probabilistic Programming

And finally, as a reference for Probabilistic Programming in general, I recommend this book, and this site. 


// Type your webPPL program here and run it using the button below. 

flip(0.9)