DOI 10.1007/s10992-010-9144-4 Explication of Inductive Probability
- Patrick Maher
Abstract Inductive probability is the logical concept of probability in ordinary language. It is vague but it can be explicated by defining a clear and precise concept that can serve some of the same purposes. This paper presents a general method for doing such an explication and then a particular explication due to Carnap. Common criticisms of Carnap’s inductive logic are examined; it is shown that most of them are spurious and the others are not fundamental.
Inductive Logic and the Justification of Induction
- Patrick Maher
Philosophy is a subject in which almost everything is disputed and very little progress is made. Why is it like that? I think the chief reason is that philosophers are concerned with vague and ambiguous concepts such as justification, knowledge, justice, virtue, free will, and personal identity. Because these concepts are vague and ambiguous, many of the questions that philosophers ask about them have no answer that is either true or false. We can describe this by saying that many questions philosophers ask are meaningless; they are what the logical empiricists called pseudo-questions. In view of this, it is not...
Evolutionary Search in Inductive Equational Logic Programming
- Lutz H Hamel
Abstract- Concept learning is the induction of a description from a set of examples. Inductive logic programming can be considered a special case of the general notion of concept learning specifically referring to the induction of first-order theories. Both concept learning and inductive logic programming can be seen as a search over all possible sentences in some representation language for sentences that correctly explain the examples and also generalize to other sentences that are part of that concept. In this paper we explore inductive logic programming with equational logic as the representation language. We present a high-level overview of the...
Exploiting Event Semantics to Parse the Rhetorical Structure of Natural Language Text
- Rajen Subba
Previous work on discourse parsing has mostly relied on surface syntactic and lexical features; the use of semantics is limited to shallow semantics. The goal of this thesis is to exploit event semantics in order to build discourse parse trees (DPT) based on informational rhetorical relations. Our work employs an Inductive Logic Programming (ILP) based rhetorical relation classifier, a Neural Network based discourse segmenter, a bottom-up sentence level discourse parser and a shift-reduce document level discourse parser. 1
Sciences A Comparative Approach with Mathematica TM Support
- P. C. Gregory
Increasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. By encompassing both inductive and deductive logic, Bayesian analysis can improve model parameter estimates by many orders of magnitude. It provides a simple and unified approach to all data analysis problems, allowing the experimenter to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. This book provides a clear exposition of the underlying concepts with large numbers of worked examples and problem sets. The book also discusses numerical techniques for implementing the Bayesian calculations, including...
Biochemical knowledge discovery using Inductive Logic Programming
- Stephen Muggleton; Ashwin Srinivasan; R. D. King; M.J.E. Sternberg
Machine Learning algorithms are being increasingly used for knowledge discovery tasks. Approaches can be broadly divided by distinguishing discovery of procedural from that of declarative knowledge. Client requirements determine which of these is appropriate. This paper discusses an experimental application of machine learning in an area related to drug design. The bottleneck here is in finding appropriate constraints to reduce the large number of candidate molecules to be synthesisedand tested. Such constraints canbe viewed as declarative specifications of the structural elements necessary for high medicinal activity and low toxicity. The first-order representation used within Inductive Logic Programming (ILP) provides an...
Using Inductive Logic Programming to construct Structure-Activity Relationships
- Ashwin Srinivasan; Ross D. King
The existence and rapid growth of chemical databases have brought into focus the utility of methods that can assist the discovery of predictive patterns in data, and communicating them in a manner designed to provoke insight. This has turned attention to machine learning techniques capable of extracting "symbolic" descriptions from data. At the cutting-edge of such techniques is Inductive Logic Programming (ILP). Given a set of observations and background knowledge encoded as a set of logical descriptions, an ILP system attempts to construct explanations for the observations. The explanations are in the same language as the observations and background knowledge...
Logic Programming and Co-Inductive Definitions
- Mathieu Jaume
This paper focuses on the assignment of meaning to infinite derivations in logic programming. Several approaches have been developped by considering infinite elements in the universe of the discourse but none are complete. By considering proofs as objects in a co-inductive set, standard properties of co-inductive definitions are used both to explain this incompleteness and to define a sound and complete semantics, based on the logic program as co-inductive denition paradigm, for a subclass of infinite derivations, called infinite derivations over a finite domain (i.e. derivations which do not compute infinite terms).
On Bounded Set Theory
- Vladimir Yu. Sazonov
We consider some Bounded Set Theories (BST), which are analogues to Bounded Arithmetic. Corresponding provably-recursive operations over sets are characterized in terms of explicit definability and PTIME- or LOGSPACE-computability. We also present some conservativity results and describe a relation between BST, possibly with Anti-Foundation Axiom, and a Logic of Inductive Definitions (LID) and Finite Model Theory.
Programming by Demonstration: An Inductive Learning Formulation
- Tessa Lau; Daniel S. Weld
Although Programming by Demonstration (PBD) has the potential to improve the productivity of unsophisticated users, previous PBD systems have used brittle, heuristic, domain-specific approaches to execution-trace generalization. In this paper we define two applicationindependent methods for performing generalization that are based on well-understood machine learning technology. TGen vs uses version-space generalization, and TGen foil is based on the FOIL inductive logic programming algorithm. We analyze each method both theoretically and empirically, arguing that TGen vs has lower sample complexity, but TGen foil can learn a much more interesting class of programs.
Warmr: A Data Mining Tool for Chemical Data
- Ross King Ashwin; Ross D. King; Ashwin Srinivasan; Luc Dehaspe
Data mining techniques are becoming increasingly important in chemistry as databases become too large to examine manually. Data mining methods from the field of Inductive Logic Programming (ILP) have potential advantages for structural chemical data. In this paper we present Warmr, the first ILP data mining algorithm to be applied to chemoinformatic data. We illustrate the value of Warmr by applying it to a well studied database of chemical compounds tested for carcinogenicity in rodents. Data mining was used to find all frequent substructures in the database, and knowledge of these frequent substructures is shown to add value to the...
A new approach to pharmacophore mapping and QSAR analysis using Inductive Logic Programming. Application to Thermolysin inhibitors and Glycogen Phosphorylase Inhibitors
- Nathalie Marchand-geneste; Kimberly A. Watson; Björn Alsberg; Ross D. King
A key problem in QSAR is the selection of appropriate descriptors to form accurate regression equations for the compounds under study. Inductive Logic Programming (ILP) algorithms are a class of machine learning algorithm that have been successfully applied to a number of SAR problems. Unlike other QSAR methods, which use attributes to describe chemical structure, ILP uses relations. This gives ILP the advantages of: not requiring explicit superimposition of individual compounds in a dataset, dealing naturally with multiple conformations, and using a language much closer to that used normally by chemists. We unify ILP and standard regression techniques to give...
Learning Three-Valued Logic Programs
- Evelina Lamma; Fabrizio Riguzzi; Luís Moniz Pereira
We show that the adoption of a three-valued setting for inductive concept learning is particularly useful for learning. Distinguishing between what is true, what is false and what is unknown can be useful in situations where decisions have to be taken on the basis of scarce information. In order to learn in a three-valued setting, we adopt Extended Logic Programs (ELP) under a Well-Founded Semantics with explicit negation (WFSX ) as the representation formalism for learning. Standard Inductive Logic Programming techniques are then employed to learn the concept and its opposite. The learnt definitions of the positive and negative concepts...
Pharmacophore Discovery using the Inductive Logic Programming System Progol
- Paul Finn; David Page; Ronny Kohavi; Foster Provost
This paper is a case study of a machine aided knowledge discovery process within the general area of drug design. More specifically, the paper describes a sequence of experiments in which an Inductive Logic Programming(ILP) system is used for pharmacophore discovery. Within drug design, a pharmacophore is a description of the substructure of a ligand (a small molecule) which is responsible for medicinal activity. This medicinal activity is produced by interaction between the ligand and a binding site on a target protein. ILP was chosen by the domain expert (first author) at Pfizer since active molecules are most naturally described,...
Feature construction with Inductive Logic Programming: a study of quantitative predictions of chemical activity aided by structural attributes
- Ashwin Srinivasan; R. D. King; Biomolecular Modelling Laboratory
Recently, computer programs developed within the field of Inductive Logic Programming have received some attention for their ability to construct restricted first-order logic solutions using problem-specific background knowledge. Prominent applications of such programs have been concerned with determining "structure-activity" relationships in the areas of molecular biology and chemistry. Typically the task here is to predict the "activity" of a compound, like toxicity, from its chemical structure.
Learning phonotactics using ILP
- Stasinos Konstantopoulos; Alfa-informatica Rijksuniversiteit Groningen
This paper describes experiments on learning Dutch phonotactic rules using Inductive Logic Programming, a machine learning discipline based on inductive logical operators. Two different ways of approaching the problem are experimented with, and compared against each other as well as with related work on the task. The results show a direct correspondence between the quality and informedness of the background knowledge and the constructed theory, demonstrating the ability of ILP to take good advantage of the prior domain knowledge available. Further research is outlined. 1
Elementos para el debate sobre la valoración de la prueba científica en España: hacia un estándar acreditable bajo la norma ISO 17.025 sobre conclusiones de informes periciales.
- Lucena Molina, José Juan; Escola García, Miguel Ángel; Pardo Iranzo, Virginia
An amendment in 2002 to the Spanish Code of Criminal Procedure converted into documentary evidence the expert reports prepared by official laboratories aimed at determining the nature, weight and purity of seized drugs; such expert reports were considered objective and reliable by default. Both the prosecution and the experts benefit from this approach, especially the latter, who are spared from appearance before the courts in most cases. This is likely to be extended to other types of forensic evidence in Spain and, therefore, it would be up to the legislator to finally decide which field of expertise should be considered...
Carnap and the logic of inductive inference
- S. L. Zabell
This chapter discusses Carnap’s work on probability and induction, using the notation and terminology of modern mathematical probability, viewed from the perspective of the modern Bayesian or subjective school of probability. (It is a much expanded and more mathematical version of [Zabell, 2007]). Carnap initially
Argument, Inquiry, and the Unity of Science
- Kevin T. Kelly
Ockham’s razor impels scientists to seek ever greater unity in nature. That seems to saddle science with a metaphysical presupposition of simplicity that might be false. The objection is apt if scientific method is understood as a system of inductive logic or proof, for then the unity of science must, somehow, function as an unjustified premise in scientific arguments. But if science is understood, instead, primarily as a process of discovery that aims at finding the truth as efficiently as possible, the unity of science can be understood as an optimally truth-conducive heuristic rather than as a metaphysical presupposition. Optimal...
Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming
- Mary Elaine Califf; Raymond J. Mooney
This paper demonstrates the capabilities of Foidl, an inductive logic programming (ILP) system whose distinguishing characteristics are the ability to produce first-order decision lists, the use of an output completeness assumption to provide implicit negative examples, and the use of intensional background knowledge. The development of Foidl was originally motivated by the problem of learning to generate the past tense of English verbs; however, this paper demonstrates its superior performance on two different sets of benchmark ILP problems. Tests on the finite element mesh design problem show that Foidl's decision lists enable it to produce better results than all other...