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Page 3342 of Mathematical Reviews Vol. , Issue 2001E [page]

2001 Mathematical Reviews  
Starting with Shi- nohara’s result on bounded finite thickness and inductive inference 68 COMPUTER SCIENCE 3342 from positive data, we investigate a broad spectrum of classes of Prolog programs inferable  ...  Summary: “In this paper, we study inferability of Prolog programs from positive examples alone.  ... 

Page 4488 of Mathematical Reviews Vol. , Issue 87h [page]

1987 Mathematical Reviews  
Bibel, Predicative programming revisited (pp. 25-40); Takeshi Shinohara, Some problems on inductive inference from positive data (pp. 41-58); E.  ...  Clark, McCabe and Gregory introduce the principal features of I(mperial)C(ollege)-PROLOG which dif- fers from PROLOG in that, e.g., it does not provide extra-logical primitives like the “slash”.  ... 

An inductive logic programming query language for database mining [chapter]

Luc De Raedt
1998 Lecture Notes in Computer Science  
The approach is motivated by the view of data mining as a querying process (see Imielinkski and Mannila, CACM 96).  ...  Because the primitives of the presented query language can easily be combined with the ?rolog programming language, complex systems and behaviour can be specified declaratively.  ...  Acknowledgements The author is supported by the Fund for Scientific Research, Flanders, and by the ESPRIT IV project no 20237 on Inductive Logic Programming II.  ... 
doi:10.1007/bfb0055898 fatcat:7k7wix3awndifapd3bzxfk5gkq

Developments from enquiries into the learnability of the pattern languages from positive data

Yen Kaow Ng, Takeshi Shinohara
2008 Theoretical Computer Science  
Angluin, Inductive inference of formal languages from positive data, Information and Control 45 (1980) 117-135].  ...  In this paper we chronologize some results that developed from the investigations on the inferability of the pattern languages from positive data.  ...  primitive Prolog programs, and showed the class of such programs to be efficiently inferable from positive data [19] .  ... 
doi:10.1016/j.tcs.2008.02.028 fatcat:wphpibt575e7rdx6rb4l6if2c4

A PROLOG environment for developing and reasoning about data types [chapter]

Jieh Hsiang, Mandayam K. Srivas
1985 Lecture Notes in Computer Science  
We also present a PROLOG-based inductive theorem proving method for proving properties of data types and correctness of implementations.  ...  We illustrate the application of the environment to the development of abstract data types in PROLOG.  ...  primitive that proves the correctness of the verification conditions and properties of PROLOG programs in general.  ... 
doi:10.1007/3-540-15199-0_18 fatcat:x64r6m7aavh2lfeajxskdtfe2e

The practice of logical frameworks [chapter]

Frank Pfenning
1996 Lecture Notes in Computer Science  
of encodings in conjunction with a system of primitive recursive functionals for higher-order data representations.  ...  A(x, y) explicitly by induction over x, we can exhibit a primitive recursive functional f such that ∀x. A(x, f(x)).  ... 
doi:10.1007/3-540-61064-2_33 fatcat:4misu6ivoncvhndnxocin3z6ha

Tunneling Neural Perception and Logic Reasoning through Abductive Learning [article]

Wang-Zhou Dai, Qiu-Ling Xu, Yang Yu, Zhi-Hua Zhou
2018 arXiv   pre-print
We demonstrate that--using human-like abductive learning--the machine learns from a small set of simple hand-written equations and then generalizes well to complex equations, a feat that is beyond the  ...  capability of state-of-the-art neural network models.  ...  Finally, the background knowledge based heuristic search allows abductive learning to automatically infer the existence of primitive objects from raw data.  ... 
arXiv:1802.01173v2 fatcat:cfmiaongovb4jaj3c4hk7g54ci

Implementing HOL in an Higher Order Logic Programming Language

Cvetan Dunchev, Claudio Sacerdoti Coen, Enrico Tassi
2016 Proceedings of the Eleventh Workshop on Logical Frameworks and Meta-Languages: Theory and Practice - LFMTP '16  
We present a proof-of-concept prototype of a (constructive variant of an) HOL interactive theorem prover written in a Higher Order Logic Programming (HOLP) language, namely an extension of λProlog.  ...  The prototype is meant to support the claim, that we reinforce, that HOLP is the class of languages that provides the right abstraction level and programming primitives to obtain concise implementations  ...  Acknowledgments We are greatly indebted with Dale Miller for long discussions over λProlog, its use for implementing interactive provers and the constraint programming extensions.  ... 
doi:10.1145/2966268.2966272 dblp:conf/lfmtp/DunchevCT16 fatcat:46lgph4pfngn7cycf2f762nwkm

Page 3642 of Mathematical Reviews Vol. , Issue 95f [page]

1995 Mathematical Reviews  
of primitive Prologs from positive data.  ...  one-sided error from positive examples only.  ... 

Probabilistic Inductive Querying Using ProbLog [chapter]

Luc De Raedt, Angelika Kimmig, Bernd Gutmann, Kristian Kersting, Vítor Santos Costa, Hannu Toivonen
2010 Inductive Databases and Constraint-Based Data Mining  
We study how probabilistic reasoning and inductive querying can be combined within ProbLog, a recent probabilistic extension of Prolog.  ...  After a short introduction to ProbLog, we provide a survey of the different types of inductive queries that ProbLog supports, and show how it can be applied to the mining of large biological networks.  ...  Probabilistic databases [1] allow one to represent and reason about uncertain data, while inductive databases [2] aim at tight integration of data mining primitives in database query languages.  ... 
doi:10.1007/978-1-4419-7738-0_10 fatcat:lpistivbwbgg5pjdq5o5orryl4

Inductive logic programming at 30 [article]

Andrew Cropper, Sebastijan Dumančić, Richard Evans, Stephen H. Muggleton
2021 arXiv   pre-print
Inductive logic programming (ILP) is a form of logic-based machine learning. The goal is to induce a hypothesis (a logic program) that generalises given training examples.  ...  As ILP turns 30, we review the last decade of research.  ...  The second dimension is whether the network is designed for big data problems [ , ] or for data-efficient learning from a handful of data items [ ].  ... 
arXiv:2102.10556v2 fatcat:kv7ktjbajng6jjfae3sq3ubbmu

Page 1730 of Mathematical Reviews Vol. , Issue 95c [page]

1995 Mathematical Reviews  
and Takeshi Shinohara, Efficient induc- tive inference of primitive Prologs from positive data (135-146); Shyam Kapur, Monotonic language learning (147-158); Yoshiaki Okubo and Makoto Haraguchi, Planning  ...  The twenty-two papers in this collection include the following: Rolf Wiehagen, From inductive inference to algorithmic learning theory (13-24); Takashi Yokomori, On learning systolic languages (41-52);  ... 

Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited

Stephen H. Muggleton, Dianhuan Lin, Alireza Tamaddoni-Nezhad
2015 Machine Learning  
Since the late 1990s predicate invention has been under-explored within inductive logic programming due to difficulties in formulating efficient search mechanisms.  ...  with respect to a modified Prolog meta-interpreter which acts as the learning engine.  ...  Acknowledgments We thank Tom Mitchell, William Cohen and Jayant Krishnamurthy for helpful discussions and data from the NELL database.  ... 
doi:10.1007/s10994-014-5471-y fatcat:5hmbbfsoc5ggdmfwrjgtcsudam

Meta-Interpretive Learning from noisy images

Stephen Muggleton, Wang-Zhou Dai, Claude Sammut, Alireza Tamaddoni-Nezhad, Jing Wen, Zhi-Hua Zhou
2018 Machine Learning  
The natural science settings involve identification of the position of the light source in telescopic and microscopic images, while the RoboCup setting involves identification of the position of the ball  ...  , such as the existence and position of light sources and other objects outside the image.  ...  The authors believe that LV has long-term potential as an AI technology with the potential for unifying the disparate areas of logical based learning with visual perception.  ... 
doi:10.1007/s10994-018-5710-8 fatcat:365vnau5drak5ek4ikc2d2pfze

A Model Towards Using Evidence from Security Events for Network Attack Analysis

Changwei Liu, Anoop Singhal, Duminda Wijesekera
2014 Proceedings of the 11th International Workshop on Security in Information Systems  
To achieve the accuracy and completeness of the evidence graph, we use Prolog inductive and abductive reasoning to correlate evidence by reasoning the causality, and use an anti-forensics database and  ...  Constructing an efficient and accurate model from security events to determine an attack scenario for an enterprise network is challenging.  ...  Datalog is a syntactic subset of Prolog.  ... 
doi:10.5220/0004980300830095 dblp:conf/sis/LiuSW14 fatcat:ufwhjmgivfgj7fdehejrakslvy
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