Expert Systems are a staple of good old-fashioned AI. Programming languages come into play to describe the data representation and reasoning capabilities of an expert system. In particular, truth-maintenance systems, and their probabilistic counterparts belief-maintenance systems, encapsulate the generic reasoning engine at the heart of an expert system.

Relevant Publications

2015

Cindy Mason. 1/2015. “Engineering Kindness: Building a Machine with Compassionate Intelligence.” International Journal of Synthetic Emotions. PDF 

2011

Judea Pearl. 2011. “The algorithmization of counterfactuals.” Annals of Mathematics and Artificial Intelligence . PDF

1994

Marco Ramoni, Alberto Riva, and Vimla L. Patel. 1/2/1994. “Probabilistic Reasoning under Ignorance.” Cognitive Science Society. PDF

Marco Ramoni and Alberto Riva. 1/1/1994. “Belief Maintenance in Bayesian Networks”. PDF

1993

Kenneth D. Forbus and Johan De Kleer. 11/1993. Building Problem Solvers. MIT Press. PDF

Marco Ramoni and Alberto Riva. 1/1/1993. “Belief Maintenance with Probabilistic Logic.” AAAI. PDF

1991

Peter Norvig. 10/1991. Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp. Morgan Kaufmann. Full text & code

1986

Brian Falkenhainer. 1986. “Towards a General-Purpose Belief Maintenance System.” UAI. PDF

1980

Randall Davis. 3/1980. “Meta-Rules: Reasoning About Control.” Artificial Intelligence. Publisher's Version

1978

Richard W. Weyhrauch. 1978. Prolegomena to a theory of formal reasoning . Stanford. PDF