Through symbolic programming, complex processes can be developed that build other more intricate processes by combining smaller units of logic or functionality. Thus, such programs can effectively modify themselves and appear to "learn", which makes them better suited for applications such as artificial intelligence, expert systems, natural language processing, and computer games.
- Michael A. Covington (2010-08-23). "CSCI/ARTI 4540/6540: First Lecture on Symbolic Programming and LISP" (PDF). University of Georgia. Archived from the original (PDF) on 2012-03-07. Retrieved 2014-12-29.
- Wolfram Language Notes for Programming Language Experts
- "Symbolic programming on Business Glossary". allbusiness.com. Retrieved 2013-11-20.