Description |
1 online resource (xi, 406 pages) : illustrations |
Series |
Lecture notes in computer science, 1611-3349 ; 7207. Lecture notes in artificial intelligence |
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LNCS sublibrary. SL 7, Artificial intelligence |
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Lecture notes in computer science ; 7207. 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.
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Contents |
Inference and Learning in Planning / Hector Geffner -- Beyond Reward: The Problem of Knowledge and Data / Richard S. Sutton -- Exploiting Constraints / Toby Walsh -- Online Bayesian Inference for the Parameters of PRISM Programs / James Cussens -- Learning Compact Markov Logic Networks with Decision Trees / Hassan Khosravi, Oliver Schulte, Jianfeng Hu and Tianxiang Gao -- Relational Networks of Conditional Preferences / (Extended Abstract) / Frédéric Koriche -- k-Optimal: A Novel Approximate Inference Algorithm for ProbLog / Joris Renkens, Guy Van den Broeck and Siegfried Nijssen -- Learning Directed Relational Models with Recursive Dependencies / Oliver Schulte, Hassan Khosravi and Tong Man -- Integrating Model Checking and Inductive Logic Programming / Dalal Alrajeh, Alessandra Russo, Sebastian Uchitel and Jeff Kramer -- Learning the Structure of Probabilistic Logic Programs / Elena Bellodi and Fabrizio Riguzzi -- Subgroup Discovery Using Bump Hunting on Multi-relational Histograms / Radomír Černoch and Filip Železný -- Inductive Logic Programming in Answer Set Programming / Domenico Corapi, Alessandra Russo and Emil Lupu -- Graph-Based Relational Learning with a Polynomial Time Projection Algorithm / Brahim Douar, Michel Liquiere, Chiraz Latiri and Yahya Slimani -- Interleaved Inductive-Abductive Reasoning for Learning Complex Event Models / Krishna Dubba, Mehul Bhatt, Frank Dylla, David C. Hogg and Anthony G. Cohn -- Predictive Sequence Miner in ILP Learning / Carlos Abreu Ferreira, João Gama and Vítor Santos Costa -- Conceptual Clustering of Multi-Relational Data / Nuno A. Fonseca, Vítor Santos Costa and Rui Camacho -- Expressive Power of Safe First-Order Logical Decision Trees / Joris J.M. Gillis and Jan Van den Bussche -- DNF Hypotheses in Explanatory Induction / Katsumi Inoue -- Variational Bayes Inference for Logic-Based Probabilistic Models on BDDs / Masakazu Ishihata, Yoshitaka Kameya and Taisuke Sato -- Relational Learning for Spatial Relation Extraction from Natural Language / Parisa Kordjamshidi, Paolo Frasconi, Martijn Van Otterlo, Marie-Francine Moens and Luc De Raedt -- Does Multi-Clause Learning Help in Real-World Applications? / Dianhuan Lin, Jianzhong Chen, Hiroaki Watanabe, Stephen H. Muggleton and Pooja Jain, et al. -- MC-TopLog: Complete Multi-clause Learning Guided by a Top Theory / Stephen H. Muggleton, Dianhuan Lin and Alireza Tamaddoni-Nezhad -- Integrating Relational Reinforcement Learning with Reasoning about Actions and Change / Matthias Nickles -- Efficient Operations in Feature Terms Using Constraint Programming / Santiago Ontañón and Pedro Meseguer -- Learning Theories Using Estimation Distribution Algorithms and (Reduced) Bottom Clauses / Cristiano Grijó Pitangui and Gerson Zaverucha -- Active Learning of Relational Action Models / Christophe Rodrigues, Pierre Gérard, Céline Rouveirol and Henry Soldano -- Knowledge-Guided Identification of Petri Net Models of Large Biological Systems / Ashwin Srinivasan and Michael Bain -- Machine Learning a Probabilistic Network of Ecological Interactions / Alireza Tamaddoni-Nezhad, David Bohan, Alan Raybould and Stephen H. Muggleton -- Kernel-Based Logical and Relational Learning with kLog for Hedge Cue Detection / Mathias Verbeke, Paolo Frasconi, Vincent Van Asch, Roser Morante and Walter Daelemans, et al. -- Projection-Based PILP: Computational Learning Theory with Empirical Results / Hiroaki Watanabe and Stephen H. Muggleton -- Comparison of Upward and Downward Generalizations in CF-Induction / Yoshitaka Yamamoto, Katsumi Inoue and Koji Iwanuma -- Polynomial Time Inductive Inference of Cograph Pattern Languages from Positive Data / Yuta Yoshimura, Takayoshi Shoudai, Yusuke Suzuki, Tomoyuki Uchida and Tetsuhiro Miyahara |
Summary |
This book constitutes the thoroughly refereed post-proceedings of the 21st International Conference on Inductive Logic Programming, ILP 2011, held in Windsor Great Park, UK, in July/August 2011. The 24 revised full papers were carefully reviewed and selected from 66 submissions. Also included are five extended abstracts and three invited talks. The papers represent the diversity and vitality in present ILP research including ILP theory, implementations, probabilistic ILP, biological applications, sub-group discovery, grammatical inference, relational kernels, learning of Petri nets, spatial learning, graph-based learning, and learning of action models |
Analysis |
Mathematical Logic and Formal Languages |
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Logics and Meanings of Programs |
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Computation by Abstract Devices |
Bibliography |
Includes bibliographical references and index |
Notes |
English |
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Online resource; title from PDF title page (SpringerLink, viewed Aug. 23, 2012) |
Subject |
Logic programming.
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Machine learning.
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Artificial intelligence.
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Artificial Intelligence
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Machine Learning
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artificial intelligence.
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Informatique.
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Artificial intelligence
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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 |
Muggleton, Stephen.
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Tamaddoni-Nezhad, Alireza.
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Lisi, Francesca A.
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LC no. |
2012942085 |
ISBN |
9783642319518 |
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3642319513 |
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