LEADER 03330nam 2200517 450 001 996574257803316 005 20240119114110.0 010 $a3-031-49299-4 024 7 $a10.1007/978-3-031-49299-0 035 $a(CKB)29449395500041 035 $a(DE-He213)978-3-031-49299-0 035 $a(MiAaPQ)EBC31051274 035 $a(Au-PeEL)EBL31051274 035 $a(EXLCZ)9929449395500041 100 $a20240119d2023 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aInductive Logic Programming $e32nd International Conference, ILP 2023, Bari, Italy, November 13-15, 2023, Proceedings /$fElena Bellodi, Francesca Alessandra Lisi, and Riccardo Zese, editors 205 $aFirst edition. 210 1$aCham, Switzerland :$cSpringer,$d[2023] 210 4$dİ2023 215 $a1 online resource (XVIII, 175 p. 40 illus., 35 illus. in color.) 225 1 $aLecture Notes in Computer Science Series ;$vVolume 14363 311 08$a9783031492983 320 $aIncludes bibliographical references and index. 327 $aDeclarative Sequential Pattern Mining in ASP -- Extracting Rules from ML models in Angluin?s Style -- A Constrained Optimization Approach to Set the Parameters of Probabilistic Answer Set Programs -- Regularization in Probabilistic Inductive Logic Programming -- Towards ILP-based LTLf passive learning -- Learning Strategies of Inductive Logic Programming Using Reinforcement Learning -- Select first, transfer later: choosing proper datasets for statistical relational transfer learning -- GNN based Extraction of Minimal Unsatisfiable Subsets -- What Do Counterfactuals Say about the World? Reconstructing Probabilistic Logic Programs from Answers to ?What if?? Queries -- Few-shot learning of diagnostic rules for neurodegenerative diseases using Inductive Logic Programming -- An Experimental Overview of Neural-Symbolic Systems -- Statistical relational structure learning with scaled weight parameters -- A Review of Inductive Logic Programming Applications for Robotic Systems -- Meta Interpretive Learning from Fractal images. 330 $aThis book constitutes the refereed proceedings of the 32nd International Conference on Inductive Logic Programming, ILP 2023, held in Bari, Italy, during November 13?15, 2023. The 11 full papers and 1 short paper included in this book were carefully reviewed and selected from 18 submissions. They cover all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches. 410 0$aLecture notes in computer science ;$vVolume 14363. 606 $aLogic programming$vCongresses 606 $aMachine learning$vCongresses 615 0$aLogic programming 615 0$aMachine learning 676 $a005.115 702 $aBellodi$b Elena 702 $aLisi$b Francesca Alessandra 702 $aZese$b Riccardo 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996574257803316 996 $aInductive Logic Programming$92804417 997 $aUNISA