Open Source Common Lisp Education Software

paip-lisp is the Common Lisp source code companion to Peter Norvig’s book Paradigms of Artificial Intelligence Programming. It contains implementations and examples from the book, covering classic AI techniques through Lisp programs. The repository includes systems for symbolic reasoning, search, rule-based inference, natural language processing, pattern matching, logic programming, and game-playing examples. It is valuable for readers who want to study the original code while working through the text or revisiting older AI ideas. The code also serves as a historical reference for how AI programming was taught before today’s deep-learning-centered ecosystem. paip-lisp is best suited for learners interested in Lisp, symbolic AI, and the foundations of practical AI programming.

Axiom is a computer algebra system. It consists of an interpreter, a compiler and a library of algorithms. Axiom is an excellent research platform as well as a useful tool for scientific programming.

OpenAxiom is an open source Computer Algebra System. It offers an interactive environment, an expressive programming language, a compiler, a large set of mathematical libraries of interest to researchers and practitioners of computational sciences.

This Project will administer an exam on an applet using 4 answer mutliple choice questions. Only one answer may be selected per question. Later we may improve this but for now this is the scope. We will use XML to read and write exams.

Lisp Koans is a self-guided learning path for Common Lisp that teaches the language’s idioms through a series of failing tests you progressively make pass. Each koan introduces a concept—symbols, lists, macros, multiple dispatch, reader syntax—then asks you to fill in the blanks and run the suite again. The feedback loop is intentionally tight: fail, reflect, fix, and rerun until the tests become a form of living documentation. Because koans are organized from fundamentals to metaprogramming, learners internalize not just syntax but also Lisp’s philosophy of code-as-data. The exercise format makes it ideal for workshops, katas, or leveling up engineers who have never touched a Lisp before. It’s minimal on infrastructure and maximal on discovery, encouraging use of a REPL and inspector while you solve each puzzle.

Implementation of raytracer with its prototype written in LISP. Goals: lisp knowledge.