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	Logic - Encyclopedia.WorldSearch (Site not responding. Last check: 2007-10-29)
		Aristotelian logic has principally been concerned with teaching good argument, and is still taught with that end today, while in mathematical logic and analytical philosophy much greater emphasis is placed on logic as an object of study in its own right, and so logic is studied at a more abstract level.
		The boldest attempt to apply logic to mathematics was undoubtedly the logicism pioneered by philosopher-logicians such as Gottlob Frege and Bertrand Russell: the idea was that mathematical theories were logical tautologies, and the programme was to show this by means to a reduction of mathematics to logic.
		Logic is extensively applied in the fields of artificial intelligence, and computer science, and these fields provide a rich source of problems in formal logic.
	encyclopedia.worldsearch.com /logic.htm (2407 words)

	Logic - Open Encyclopedia (Site not responding. Last check: 2007-10-29)
		In ordinary language, logic is the reasoning used to reach a conclusion from a set of assumptions.
		More formally, logic is the study of inference—the process whereby new assertions are produced from already established ones.
		As such, of particular concern in logic is the structure of inference—the formal relations between the newly produced assertions and the previously established ones, where "formal" means that the relations are independent of the assertions themselves.
	open-encyclopedia.com /Logic (2307 words)

	Inductive logic programming (Site not responding. Last check: 2007-10-29)
		Inductive logic programming (ILP) is a machine learning approach, which uses techniques of logic programming.
		From a database of facts and expected results, which are divided into positive andnegative examples, an ILP system tries to derive a logic program that proves all the positive and none of the negativeexamples.
		Inductive logic programming is particularly useful in natural language processing.
	www.therfcc.org /inductive-logic-programming-165069.html (97 words)

	Inductive Logic Programming
		The development of Inductive Logic Programming has been heavily formal (mathematical) in nature, because the major people in the field believe that this is the only way to progress and to show progress.
		As a final notation, it is important to remember that a logic program can contain just one Horn clause, and that the Horn clause could have no body, in which case the head of the clause is a known fact about the domain.
		ILP systems were used to determine rules for the mesh resolution of edges in the structure in terms of certain properties of the structure being modelled.
	www.doc.ic.ac.uk /~sgc/teaching/v231/lecture14.html (4223 words)

	Inductive Logic Programming
		Inductive Logic Programming (ILP) is a research area formed at the intersection of Machine Learning and Logic Programming.
		The theory of ILP is based on proof theory and model theory for the first order predicate calculus.
		Inductive hypothesis formation is characterised by techniques including inverse resolution, relative least general generalisations, inverse implication, and inverse entailment.
	www.cs.york.ac.uk /mlg/ilp.html (316 words)

	The World Wide Web Virtual Library: Logic Programming (Site not responding. Last check: 2007-10-29)
		Inductive Logic Programming (ILP): ILPNET is the Inductive Logic Programming European Scientific Network.
		Logic Program Synthesis and Transformation EC Human Capital and Mobility programme.
		Mercury, a pure logic programming language designed for the development of efficient and robust real-world applications, based on strong types and modes.
	archive.comlab.ox.ac.uk /logic-prog.html (1423 words)

	Research grant: Inductive Logic Programming (Site not responding. Last check: 2007-10-29)
		Inductive logic programming (ILP) is the intersection of inductive learning and logic programming.
		The main long term technical goal of the ILP project is to update the techniques of the classical empirical learning paradigm to a logic programming framework.
		In this way ILP aims to overcome the two main limitations of classical empirical or similarity based learning algorithms, such as the TDIDT-family: the use of a limited knowledge representation formalism (essentially a propositional logic), and the inability to use substantial background knowledge in the learning process.
	web.comlab.ox.ac.uk /oucl/research/grants/hw.html (438 words)

	Inductive Logic Programming (Site not responding. Last check: 2007-10-29)
		Inductive Logic Programming (ILP) is a method by which a computer program can learn concepts by example.
		The concept is represented in Horn clause logic, the same representation as a Prolog program.
		ILP is now used in applications such as protein folding prediction, drug design and finite element analysis.
	www.cse.unsw.edu.au /~claude/research/ilp.html (784 words)

	Inductive Logic Programming - Theory (Site not responding. Last check: 2007-10-29)
		Inductive inference is, in a sense, the inverse of deduction.
		Inductive inference based on inverting resolution in propositional logic was the basis of the inductive inference rules within the Duce system.
		ILP system require the ability to learn and make use of general constraints, rather than requiring large numbers of ground negative examples.
	web.comlab.ox.ac.uk /oucl/research/areas/machlearn/ilp_theory.html (2104 words)

	The World Wide Web Virtual Library: Logic Programming (Site not responding. Last check: 2007-10-29)
		Papers on logic programming in computer science journals (authors/titles only) and technical reports (abstracts).
		Logic programming meeting proceedings bibliographies in BibTeX format from DFKI Programming Systems Lab.
		Sources for Prolog and other related logic programming systems including constraint and parallel Prolog system implementations are available.
	www.comlab.ox.ac.uk /archive/logic-prog.html (1423 words)

	Inductive Logic Programming (Site not responding. Last check: 2007-10-29)
		Because the language of Horn-clause logic is more expressive than the other concept description languages we have seen, it is now possible to learn far more complex concepts than was previously possible.
		Powerful induction programs that use expressive languages may be a vital aid in discovering useful patterns in all these data.
		Training data for the program was 44 trimethoprim analogues and their observed inhibition of E. coli dihydrofolate reductase.
	www.cse.unsw.edu.au /~claude/teaching/AI/notes/ml/07ilp/07ilp.html (1334 words)

	ILP2004 (Site not responding. Last check: 2007-10-29)
		Inductive Logic Programming (ILP) is a form of relational learning that is at the cutting-edge of extracting symbolic descriptions from data.
		ILP systems have, in the past, been used with success on difficult problems in the sciences, engineering, language understanding and the arts.
		ILP 2004 is the fourteenth in a series of international conferences on ILP.
	ilp.fe.up.pt (122 words)

	GSLT: Machine Learning: ILP page
		Logic, Programming and Prolog (2ed) by Ulf Nilsson and Jan Małuszyński.
		An introduction to inductive logic programming and learning language in logic.
		For example, in the ILP section we discuss subsumption, inverse resolution, least general generalisation, relative least general generalisation, inverse entailment, saturation, refinement and abduction.
	www-users.cs.york.ac.uk /~jc/teaching/GSLT/ilp-goth.html (557 words)

	ILPnet2
		Welcome to the homepage of ILPnet2, which officially started 1st September 1998, and was funded for 4 years under the European Union's INCO program until 31 August 2002.
		To co-ordinate ILP research among the nodes of the network.
		To disseminate information on ILP research and applications to the outside world, including both academic and industrial/non-academic institutions.
	www.cs.bris.ac.uk /~ILPnet2 (376 words)

	8th Int. Conf. on Inductive Logic Programming (ILP'98) (Site not responding. Last check: 2007-10-29)
		Inductive Logic Programming (ILP) is the study of automated inductive learning where the knowledge representation used is first-order definite clause logic.
		The richness of the representation makes ILP particularly well-suited to domains such as organic chemistry and molecular biology, natural language processing, and telecommunications, where examples are easily described as sets of objects (e.g., atoms in a molecule) together with relations that hold among those objects (e.g., bonds or distance relations).
		For additional information on inductive logic programming, you can follow links to the program chair's and program committee members' web sites (click on their highlighted names above), or go to the ILPNET website.
	www.cs.wisc.edu /~dpage/ilp98.html (183 words)

	UT ML Group: Natural Language Learning
		Inductive Logic Programming (ILP) is the intersection of Machine Learning and Logic Programming in which the learner's hypothesis space is the set of logic programs.
		Cocktail is a new ILP algorithm for inducing semantic parsers.
		ILP algorithms, which learn relational (first-order) rules, are used in a parser acquisition system called CHILL that learns rules to control the behavior of a traditional shift-reduce parser.
	www.cs.utexas.edu /users/ml/publication/nl-abstracts.html (9295 words)

	Esprit LTR 20237 Inductive Logic Programming II (ILP2) Home Page (Site not responding. Last check: 2007-10-29)
		Inductive logic programming (ILP) is a research area lying at the intersection of inductive machine learning and logic programming.
		The general aim of ILP is to develop theories, techniques and applications of inductive learning from observations and background knowledge in a first order logical framework.
		This project aims at continuing the ILP 1 project in which several significant research results have been obtained.
	www.cs.kuleuven.ac.be /~ml/esprit/esprit.ilp2.20237.html (297 words)

	C. David Page Jr.
		Of particular interest are inductive logic programming (ILP) and other multi-relational learning techniques capable of dealing with complex data points (such as molecules) and producing logical rules (such as the rules in green to the side).
		Inductive Logic Programming (ILP) is the study of automated inductive learning where the knowledge representation used is first-order definite clause logic (as embodied in the language Prolog).
		Because of the close correspondence between logic and databases (relational algebra is equivalent to Datalog, a simplification of Prolog), ILP is a leading approach to Multi-relational Data Mining, or directly mining databases with multiple relational tables.
	www.cs.wisc.edu /~dpage (1810 words)

	Inductive Logic Programming - Theory
		In contrast, a 'V' inductive inference step derives one of the clauses on the arm of the `V' given the clause on the other arm and the clause at the base.
		Current ILP systems perform poorly in the presence of relevant long chains of literals, connected by shared variables.
		ILP systems have severe restrictions on the form of numeric constraints that can be used.
	www.doc.ic.ac.uk /~shm/ilp_theory.html (2111 words)

	The World Wide Web Virtual Library: Logic Programming (Site not responding. Last check: 2007-10-29)
		Logic Programming available around the world on the World Wide Web.
		Logic Programming Research Groups listed by the Databases and Logic Programming (DBLP) computer science bibliography server.
		Fish, a logic programmer's shell available under the GNU general public licence.
	vl.fmnet.info /logic-prog (1454 words)

	Workshop on Logic and Learning (Site not responding. Last check: 2007-10-29)
		Logic has been used as the underlying representation language in many areas of AI including machine learning.
		Learnability of logical expressions has been studied in many paradigms including PAC learning, query based learning, inductive inference, and inductive logic programming.
		There are theoretical results on learning in propositional logic as well as for logic programs, description logic, and fragments of first-order logic.
	www.eecs.tufts.edu /~roni/LicsWksp (287 words)

	Learning in Clausal Logic: A Perspective on Inductive Logic Programming
		In: Computational Logic: Logic Programming and Beyond (Essays in Honour of Robert A. Kowalski), Antonis C. Kakas and Fariba Sadri, editors, volume LNAI 2407, pages 437--471.
		Inductive logic programming is a form of machine learning from examples which employs the representation formalism of clausal logic.
		The chapter gives an accessible introduction to the main issues in inductive logic programming.
	www.cs.bris.ac.uk /Publications/pub_info.jsp?id=1000649 (141 words)

	ILP2000: Tenth International Conference on Inductive Logic Programming
		This is the tenth conference in the highly succesful series of International Workshops/Conferences on Inductive Logic Programming, which has run anually since 1991.
		Inductive logic programming (ILP) is built on foundations laid by research in other areas of computational logic.
		The purpose of this talk is to interest researchers from other areas of computational logic in contributing their special skill sets to help ILP meet these challenges.
	www.cs.york.ac.uk /ILP-events/ILP-2000 (560 words)

	CV 2004 (Site not responding. Last check: 2007-10-29)
		Using logical decision trees for clustering, Proceedings of the IJCAI-97 Workshop on Frontiers of Inductive Logic Programming (De Raedt, L. and Muggleton, S., eds.), pp.
		Inductive constraint logic and the mutagenesis problem, Proceedings of the Eighth Dutch Conference on Artificial Intelligence (L. J.-J.Ch.
		Inductive constraint logic and the mutagenesis problem, Proceedings of the 5th Belgian-Dutch Conference on Machine Learning, 1995, pp.
	www.cs.kuleuven.ac.be /%7Ehendrik/cv_ext.html (4262 words)

	Inductive Logic Programming (ResearchIndex)
		Abstract: Inductive Logic Programming (ILP) can be viewed as research in the intersection of Logic Programming and inductive Machine Learning.
		Informally speaking the field is concerned with the induction of PROLOG programs.
		Being able to express the discovered knowledge in a first-order logic representation language can overcome some of the limitations of classical learning algorithms.
	citeseer.ist.psu.edu /52020.html (453 words)

	CL2000
		The CL series is sponsored by the Association for Logic Programming and the ESPRIT Network of Excellence in Computational Logic.
		Papers on all aspects of the theory, implementation, and application of Computational Logic are requested, where Computational Logic is to be understood broadly as the use of logic in Computer Science.
		However, a paper considered to be out of scope by the Chair of the stream to which the paper was submitted and the Program Chair may be sent to another stream (after notifying the author) or else returned to the author, if no stream is appropriate.
	www.doc.ic.ac.uk /cl2000 (352 words)

	Department of Computer Science / ILP Course 2000 (Site not responding. Last check: 2007-10-29)
		Logic has always been very popular as a knowledge representation formalism and the maturity of logic programming tools enables its use in many application domains.
		This course is an introduction to Inductive Logic Programming when it is used for Knowledge Discovery from Databases (KDD).
		From the Inductive Logic Programming point of view, the course aims at giving an overview of the field, with an emphasis on the so-called "learning from interpretations" scheme.
	www.cs.helsinki.fi /u/mklemett/ILPcourse2000 (828 words)

	William W. Cohen's Papers: Inductive Logic Programming (Site not responding. Last check: 2007-10-29)
		William W. Cohen (1995): Pac-learning recursive logic programs: Efficient algorithms in J.
		William W. Cohen (1993): Cryptographic limitations on learning one-clause logic programs in AAAI 1993: 80-85.
		William W. Cohen (1993): Pac-learning a restricted class of recursive logic programs in AAAI 1993: 86-92.
	www.cs.cmu.edu /~wcohen/pubs-i.html (388 words)

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