| Description |
1 online resource (x, 272 pages) : illustrations |
| Series |
Lecture notes in computer science, 1611-3349 ; 7842. Lecture notes in artificial intelligence |
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LNCS sublibrary. SL 7, Artificial intelligence |
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Lecture notes in computer science ; 7842. 1611-3349
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Lecture notes in computer science. Lecture notes in artificial intelligence
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LNCS sublibrary. SL 7, Artificial intelligence.
|
| Contents |
A Relational Approach to Tool-Use Learning in Robots / Solly Brown, Claude Sammut -- A Refinement Operator for Inducing Threaded-Variable Clauses / Angelos Charalambidis, Stasinos Konstantopoulos -- Propositionalisation of Continuous Attributes beyond Simple Aggregation / Soufiane El Jelali, Agnès Braud, Nicolas Lachiche -- Topic Models with Relational Features for Drug Design / Tanveer A. Faruquie, Ashwin Srinivasan, Ross D. King -- Pairwise Markov Logic / Daan Fierens, Kristian Kersting, Jesse Davis, Jian Chen -- Evaluating Inference Algorithms for the Prolog Factor Language / Tiago Gomes, Vítor Santos Costa -- Polynomial Time Pattern Matching Algorithm for Ordered Graph Patterns / Takahiro Hino, Yusuke Suzuki, Tomoyuki Uchida, Yuko Itokawa -- Fast Parameter Learning for Markov Logic Networks Using Bayes Nets / Hassan Khosravi -- Bounded Least General Generalization / Ondřej Kuželka, Andrea Szabóová, Filip Železný -- Itemset-Based Variable Construction in Multi-relational Supervised Learning / Dhafer Lahbib, Marc Boullé, Dominique Laurent -- A Declarative Modeling Language for Concept Learning in Description Logics / Francesca Alessandra Lisi -- Identifying Driver's Cognitive Load Using Inductive Logic Programming / Fumio Mizoguchi, Hayato Ohwada, Hiroyuki Nishiyama -- Opening Doors: An Initial SRL Approach / Bogdan Moldovan, Laura Antanas, McElory Hoffmann -- Probing the Space of Optimal Markov Logic Networks for Sequence Labeling / Naveen Nair, Ajay Nagesh, Ganesh Ramakrishnan -- What Kinds of Relational Features Are Useful for Statistical Learning? / Amrita Saha, Ashwin Srinivasan, Ganesh Ramakrishnan -- Learning Dishonesty / Chiaki Sakama -- Heuristic Inverse Subsumption in Full-Clausal Theories / Yoshitaka Yamamoto, Katsumi Inoue, Koji Iwanuma -- Learning Unordered Tree Contraction Patterns in Polynomial Time / Yuta Yoshimura, Takayoshi Shoudai |
| Summary |
This book constitutes the thoroughly refereed post-proceedings of the 22nd International Conference on Inductive Logic Programming, ILP 2012, held in Dubrovnik, Croatia, in September 2012. The 18 revised full papers were carefully reviewed and selected from 41 submissions. The papers cover the following topics: propositionalization, logical foundations, implementations, probabilistic ILP, applications in robotics and biology, grammatical inference, spatial learning and graph-based learning |
| Analysis |
Computer science |
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Logic design |
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Artificial intelligence |
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Mathematical Logic and Formal Languages |
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Programming Techniques |
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Logics and Meanings of Programs |
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Computation by Abstract Devices |
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computerwetenschappen |
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computer sciences |
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programmeren |
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programming |
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kunstmatige intelligentie |
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wiskunde |
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mathematics |
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logica |
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logic |
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computational science |
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Information and Communication Technology (General) |
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Informatie- en communicatietechnologie (algemeen) |
| Bibliography |
Includes bibliographical references and author index |
| Notes |
Online resource; title from PDF title page (SpringerLink, viewed July 19, 2013) |
| Subject |
Logic programming -- Congresses
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Induction (Logic) -- Congresses
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Machine learning -- Congresses
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Logic.
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Logic
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Software
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logic.
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software.
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Logic
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Induction (Logic)
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Logic programming
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Machine learning
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| Genre/Form |
proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
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| Author |
Riguzzi, Fabrizio.
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Železný, Filip.
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| ISBN |
9783642388125 |
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3642388124 |
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