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Everything about Inductive programming
Area of automatic programming
Inductive programming (IP) is a special area of automatic programming, covering research from artificial intelligence and programming, which addresses learning of typically declarative and often recursive programs from incomplete specifications, such as input/output examples or constraints. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Inductive programmingA 5-minute orientation
- Skim a recent paper: Neuro-Symbolic Inductive Logic Programming with Logical Neural NetworksInfluential work since 2022
- Pick up a classic book: Inductive Logic ProgrammingThe most-reprinted book on the subject
- Read the landmark paper: Inductive Logic Programming: Theory and methodsCited 916 times
- Go sideways: Inductive logic programmingA closely related topic
- Go sideways: Stephen MuggletonA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Inductive Logic Programming: Theory and methods
Inductive logic programming
Applications of inductive logic programming
The Connectionist Inductive Learning and Logic Programming System
Inductive programming meets the real world
Inductive functional programming using incremental program transformation
Inductive Logic Programming At 30: A New Introduction
Regularization approach to inductive genetic programming
🆕 Influential since 2022
Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks
A Critical Review of Inductive Logic Programming Techniques for Explainable AI
Conflict-Driven Inductive Logic Programming
A differentiable first-order rule learner for inductive logic programming
Encoding inductive invariants as barrier certificates: Synthesis via difference-of-convex programming
📚 Books worth reading
Inductive Logic ProgrammingFabrizio Riguzzi · 2013
Latest Advances in Inductive Logic ProgrammingStephen Muggleton, Hiroaki Watanabe · 2014- 📕Expert-gate algorithmVarad Vidyadhar Joshi · 1992
Inductive logic programmingILP 2007 (2007 Corvallis, Or.) · 2008
Inductive logic programmingStephen Muggleton · 1992
Advances in inductive logic programmingLuc de Raedt · 1996
Inductive Logic ProgrammingKatsumi Inoue, Hayato Ohwada · 2003
IC layout basicsChristopher Saint, Judy Saint · 2001
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Inductive logic programming Inductive logic programming (ILP) is a subfield of symbolic artificial intelligence which uses logic programming as a uniform representation for examples…
- Stephen Muggleton Stephen H. Muggleton (born 6 December 1959, son of Louis Muggleton) is Professor of Machine Learning and Head of the Computational Bioinformatics Laboratory…
- Progol Progol is an implementation of inductive logic programming that combines inverse entailment with general-to-specific search through a refinement graph…
- Statistical relational learning Statistical relational learning (SRL) is a subdiscipline of artificial intelligence and machine learning that is concerned with domain models that exhibit…
- Probabilistic logic programming Probabilistic logic programming is a programming paradigm that combines logic programming with probabilities. Most approaches to probabilistic logic programming…
- Action model learning Action model learning (sometimes abbreviated action learning) is an area of machine learning concerned with the creation and modification of a software…
- Kristian Kersting Kristian Kersting (born November 28, 1973, in Cuxhaven, Germany) is a German computer scientist. He is Professor of Artificial intelligence and Machine…
- Michael Genesereth Michael Genesereth (born 1948) is an American logician and computer scientist, who is most known for his work on computational logic and applications of…