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Inductive logic started to take a clearer shape in the early 20th century in the work of William Ernest Johnson and John Maynard Keynes, and was further developed by Rudolf Carnap. Carnap introduced the distinction between pure and applied inductive logic, [ 1 ] and the modern Pure Inductive Logic evolves along the lines of the pure ...
This was considered a landmark application for inductive logic programming, as a general purpose inductive learner had discovered results that were both novel and meaningful to domain experts. [ 4 ] Progol proved very influential in the field, and the widely-used inductive logic programming system Aleph builds directly on Progol.
Inductive logic programming has adopted several different learning settings, the most common of which are learning from entailment and learning from interpretations. [16] In both cases, the input is provided in the form of background knowledge B, a logical theory (commonly in the form of clauses used in logic programming), as well as positive and negative examples, denoted + and respectively.
Inductive reasoning refers to a variety of methods of reasoning in which broad generalizations or principles are derived from a set of observations. [1] [2] Unlike deductive reasoning (such as mathematical induction), where the conclusion is certain, given the premises are correct, inductive reasoning produces conclusions that are at best probable, given the evidence provided.
The input to Aleph is background knowledge, specified as a logic program, a language bias in the form of mode declarations, as well as positive and negative examples specified as ground facts. [2] As output it returns a logic program which, together with the background knowledge, entails all of the positive examples and none of the negative ...
Inductive programming (IP) is a special area of automatic programming, covering research from artificial intelligence and programming, which addresses learning of typically declarative (logic or functional) and often recursive programs from incomplete specifications, such as input/output examples or constraints.
Kant nominated and explored the possibility of a transcendental logic with which to consider the deduction of the a priori in its pure form. Space, time and causality are considered pure a priori intuitions. Kant reasoned that the pure a priori intuitions are established via his transcendental aesthetic and transcendental logic.
Golem is an inductive logic programming algorithm developed by Stephen Muggleton and Cao Feng in 1990. [1] It uses the technique of relative least general generalisation proposed by Gordon Plotkin, leading to a bottom-up search through the subsumption lattice. [2]