Lots of nice, bite-size results.
(See Learning for learning results.)
and Russell Greiner
Artificial Intelligence, 61:1 (1993) 41--52.
The book under review here, "Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project", describes progress so far in an attempt to build a system that is intended to exhibit general common-sense reasoning ability. This review first discusses aspects of the Cyc system, with a focus on important decisions made in designing its knowledge representation language, and on how claims about the performance of the system might be validated. The review then turns to the book itself, discussing both its merits and its faults.
Russell Greiner, Barbara A. Smith and R. W. Wilkerson
Artificial Intelligence, 41:1 (79--88), November 1989.
[Reprinted in Readings in Model-based Diagnosis, edited by W. Hamscher, J. deKleer and L. Console, Morgan Kaufmann, 1992.]
Reiter  has developed a general theory of diagnosis based on first principles. His algorithm computes all diagnoses which explain the differences between the predicted and observed behavior of a given system. Unfortunately, Reiter's description of the algorithm is incorrect in that some diagnoses can be missed under certain conditions. This note presents a revised algorithm and a proof of its correctness.
Yan Xiao and Russell Greiner
Proceedings of Third UNB Artificial Intelligence Workshop, Oct 1990.
This paper describes the architecture of an efficient plan verifier that can first detect faults in a planner's plans and use these observed errors to identify possible problems in the planner's knowledge base and suggest appropriate corrections.