Python implementations of some of the classic AI programs from Peter Norvig's fantastic textbook "Paradigms of Artificial Intelligence Programming."
This is meant to be a learning resource for beginning AI programmers. It is no longer common for students to have a background in Lisp programming, as many universities have replaced Lisp with other languages in introductory programming and introductory artificial intelligence courses. It is my hope that making the programs from PAIP available in a commonly-taught language will provide a useful hands-on resource for beginning AI students.
I am writing these programs while reading through PAIP, so consider this a work in progress. Additionally, I am not at this time focusing on the end-of-chapter exercises, which typically propose extensions to the programs to avoid various limitations. I hope that these Python programs are clean translations and don't try to force Lisp idioms onto Python.
You can follow the progress of the project on Trello.
- You need Python 2.7
- Download the paip-python code.
- Type
python run_examples.pyand follow the prompts to run the examples. - To use the Prolog interpreter, run
./prolog.py. Run it with the-hoption for more details on its use and capabilities.
Literate programming-style documentation is available by running python build_docs.py or on the web at http://dhconnelly.com/paip-python. Each major
program is documented, containing an overview of its design and implementation
as well as links to example programs that use the algorithms it provides.
These programs were written by Daniel Connelly as an independent project supervised by Professor Ashok Goel.