PROGOL
A PROGOL is an Inductive Logic Programming that ...
- Context:
- branch-and-bound, using P-N-l to score
- uses saturation to restrict search space.
- See: Top-Down Learning, Prolog, Inductive Logic Programming, Ehud Shapiro, Ross Quinlan, First Order Inductive Learner, A*.
References
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/PROGOL Retrieved:2015-3-29.
- Progol is an implementation of Inductive Logic Programming used in computer science that combines "Inverse Entailment" with "general-to-specific search" through a refinement graph. [1] "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 (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.
- Progol is an implementation of Inductive Logic Programming used in computer science that combines "Inverse Entailment" with "general-to-specific search" through a refinement graph. [1] "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.