In Lehnert,W. and Ringle,M. (Eds.), Strategies for Natural Language Processing, pp. 149–176. Lawrence Erlbaum.

A knowledge-based programming system can utilize a very-high-level self description to rewrite and improve itself. This paper presents a specification, in the very-high-level language V, of the rule compiler component of the CIII knowledgebased programming system. From this specification of part of itself, CIII produces an efficient program satisfying the specification. This represents a modest application of a machine intelligence system to a real programming problem, namely improving one of the programming environment's tools — the rule compiler. The high-level description and the use of a programming knowledge base provide potential for system performance to improve with added knowledge.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.

This work investigates the use of formal logic as a practical tool for describing the syntax and semantics of a subset of English, and building a computer program to answer data base queries expressed in that subset. To achieve an intimate connection between logical descriptions and computer programs, all the descriptions given are in the definite clause subset of the predicate calculus, which is the basis of the programming language Prolog. The logical descriptions run directly as efficient Prolog programs. Three aspects of the use of logic in natural language analysis are covered: formal representation of syntactic rules by means of a grammar formalism based on logic, extraposition grammars;. formal semantics for the chosen English subset, appropriate for data base queries; informal semantic and pragmatic rules to translate analysed sentences into their formal semantics. On these three aspects, the work improves and extends earlier work by Colmerauer and others, where the use of computational logic in language analysis was first introduced. The University of Edinburgh

AJCL 8(1): 165-176, (reprinted in RNLP: 293-312)

The notion of an ethical machine can be interpreted in more than one way. Perhaps the most important interpretation is a machine that can generalize from existing literature to infer one or more consistent ethical systems and can work out their consequences. An ultra-intelligent machine should be able to do this, and that is one reason for not fearing it.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.

ACM Computing Surveys, 14(l), March

This paper presents generalizations of Bayes likelihood-ratio updating rule which facilitate an asynchronous propagation of the impacts of new beliefs and/or new evidence in hierarchically organized inference structures with multi-hypotheses variables. The computational scheme proposed specifies a set of belief parameters, communication messages and updating rules which guarantee that the diffusion of updated beliefs is accomplished in a single pass and complies with the tenets of Bayes calculus.Proc AAAI

Discourse Processes, vol. 5, No. 1, pp. 1-32.

Computational Linguistics, 8 (3-4), 139-49.

In Clarke, M. R. B. (Ed.), Advances in Computer Chess 3, pp. 45–54. Pergamon.