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Progol deals with noisy data by using a compression measure to trade off the description of errors against the hypothesis description length. Progol allows arbitrary
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Inverse entailment is used with mode declarations to derive the bottom clause, the most-specific clause within the mode language which
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Progol proved very influential in the field, and the widely-used inductive logic programming system
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programs as background knowledge and arbitrary definite clauses as examples.
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a given example. This clause is used to guide a refinement-graph search.
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Srinivasan, A.; Muggieton, S.H.; Sternberg, M.J.E.; King, R.D. (1996).
277:. Lecture Notes in Computer Science. Vol. 1314. pp. 358β376.
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in 1995. In 1996, it was used by Ashwin
Srinivasan, Muggleton,
373:"Inductive Logic Programming At 30: A New Introduction"
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Muggleton, S. (1995). "Inverse entailment and progol".
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Cropper, Andrew; DumanΔiΔ, Sebastijan (15 June 2022).
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Muggleton, S. (1997). "Learning from positive data".
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200:. This was considered a landmark application for
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377:Journal of Artificial Intelligence Research
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349:Logical and Relational Learning
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192:and Ross King to predict the
325:10.1016/0004-3702(96)81369-5
211:builds directly on Progol.
429:Inductive logic programming
275:Inductive Logic Programming
202:inductive logic programming
124:inductive logic programming
101:Inductive logic programming
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184:Progol was introduced by
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53:4.4 / 16 May 2009
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283:10.1007/3-540-63494-0_65
230:New Generation Computing
122:is an implementation of
18:Not to be confused with
312:Artificial Intelligence
198:nitroaromatic compounds
149:Unlike the searches of
347:De Raedt, Luc (2008),
155:model inference system
55:; 15 years ago
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252:10.1007/BF03037227
128:inverse entailment
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157:(MIS) and
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194:mutagenic
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138:Features
383:: 808.
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174:Prolog
120:Progol
103:system
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