PROGOL

Progol is Stephen Muggleton's implementation of inductive logic programming used in computer science that combines "Inverse Entailment" with "general-to-specific search" through a refinement graph.[1][2][3] "Inverse Entailment" is used with mode declarations to derive the most-specific clause within the mode language which entails a given example. This clause is used to guide a refinement-graph search.

Unlike the searches of Ehud Shapiro's model inference system[4] (MIS) and J. Ross Quinlan's FOIL Progol's search is efficient and has a provable guarantee of returning a solution having the maximum "compression" in the search-space. To do so it performs an admissible A*-like search, guided by compression, over clauses which subsume the most specific clause.

Progol deals with noisy data by using the "compression measure" to trade-off the description of errors against the hypothesis description length. Progol allows arbitrary Prolog programs as background knowledge and arbitrary definite clauses as examples. Despite this bench-tests show that the efficiency of Progol compares favourably with FOIL.

References
  1. Muggleton, S. (1995). "Inverse entailment and progol". New Generation Computing. 13 (3–4): 245–286. CiteSeerX 10.1.1.31.1630. doi:10.1007/BF03037227.
  2. Progol page at Imperial College
  3. Muggleton, S. (1997). "Learning from positive data". Inductive Logic Programming. Lecture Notes in Computer Science. 1314. pp. 358–376. doi:10.1007/3-540-63494-0_65. ISBN 978-3-540-63494-2.
  4. https://dl.acm.org/doi/10.5555/1623264.1623364 The model inference system, 1981


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