It provides inference and explanation facilities, and incorporates a novel form of plausible inference. YAPES is a specialized interpreter for logic programs. Figure 1 illustrates its top level structure. A PROLOG interpreter (or compiler) executes such programs consisting of sets of Horn clauses, a form of first-order logic. The YAPES system also executes such programs, as well as programs in an extended version of Horn clause logic which uses certainties as truth values, rather than just true and false.

The particular task in question is the interpretation of the electrical signals generated by the heart muscle, known as the electrocardiographic (Eco) interpretation.

A thunderstorm is considered severe if any one of the following phenomena accompanies the thunderstorm (and is reported): - tornadoes (intense, small-scale cyclones); - hailstones cm (in.) in diameter; - surface wind gusts in excess of 93 km h-1 (50 knots) and/or significant wind damage.

Such methods can effectively and efficiently induce good descriptions from a given set of examples and, optionally, induce counter-examples (for example Michalski, 1975, 1980a; Quinlan, 1979; Langley et al., 1983). These methods cannot modify concept descriptions which are contradicted by new examples, but must re-learn the descriptions from scratch. In contrast, incremental learning methods modify concept descriptions to accommodate new learning events (Winston, 1975; Michalski and Larson, 1978). When we observe human learning we clearly see that it is incremental.

It is a rich source of difficult and challenging problems which involve issues of knowledge representation, the analysis of natural language, and the automation of practical and common-sense reasoning.

This paper describes some work on automatically generating finite counterexamples in topology, and the use of counterexamples to speed up proof discovery in intermediate analysis, and gives some examples theorems where human provers are aided in proof discovery by the use of examples.

Work of the Soviet school (approximately half the book) in this explosively growing area of machine intelligence is thus made accessible for the first time to Western readers, in addition to the latest Western advances. The emergent theme of knowledge-representation is supported on the theoretical and experimental sides by recent work in inductive inference and theory-formation.

K. A. BOWEN 421 22 Higher-order extensions to PROLOG: are they needed?

This paper has three themes: (1) The task of acquiring and organizing the knowledge on which to base an expert system is difficult.

AL3 (Advice Language 3) is a problem-solving system whose structure facilitates the implementation of knowledge for a chosen problem-domain in terms of plans for solving problems, pieces-of-advice', patterns, motifs, etc. AL3 is a successor of ALI and AL 1.5 (Michie 1976, Bratko & Michie 1980a, I980b, Mozetic 1979). Experiments in which AU was applied to chess endgames established that it is a powerful tool for representing search heuristics and problem-solving strategies. The power of ALI lies mainly in the use of a fundamental concept of AU: piece-of-advice. A piece-of-advice suggests what goal should be achieved next while preserving some other condition. If this goal can be achieved in a given problem-situation (e.g. a given chess position) then we say that the piece-ofadvice is'satisfiable' in that position.