Foundations of Probabilistic Logic Programming. Languages, Semantics, Inference and Learning

Description

Contents......Page 3 Foreword......Page 8 Preface......Page 10 Figures......Page 12 Tables......Page 16 Examples......Page 17 Definitions......Page 21 Theorems......Page 23 Abbreviations......Page 25 Symbols......Page 26 Orders, Lattices, Ordinals......Page 28 Mappings & Fixpoints......Page 30 Logic Programming......Page 31 Semantics for Normal Logic Programs......Page 40 Probability Theory......Page 50 Probabilistic Graphical Models......Page 59 Languages with the Distribution Semantics......Page 68 The Distribution Semantics for Programs without Function Symbols......Page 72 Examples of Programs......Page 77 Equivalence of Expressive Power......Page 83 Translation to Bayesian Networks......Page 85 Generality of Distribution Semantics......Page 89 Extensions of Distribution Semantics......Page 91 CP-Logic......Page 93 Semantics for Non-sound Programs......Page 98 KBMC Probabilistic Logic Programming Languages......Page 103 Other Semantics for PLP......Page 107 Other Semantics for Probabilistic Logics......Page 111 Semantics with Function Symbols......Page 117 The Distribution Semantics for Programs with Function Symbols......Page 118 Infinite Covering Set of Explanations......Page 123 Comparison with Sato & Kameya Definition......Page 136 Hybrid ProbLog......Page 140 Distributional Clauses......Page 143 Extended PRISM......Page 149 cplint Hybrid Programs......Page 151 Probabilistic CLP......Page 155 Exact Inference......Page 170 PRISM......Page 171 Knowledge Compilation......Page 175 ProbLog1......Page 176 cplint......Page 180 SLGAD......Page 182 PITA......Page 183 ProbLog2......Page 188 Compilation......Page 201 Modeling Assumptions in PITA......Page 203 Inference for Queries with infinite Number of Explanations......Page 211 Inference for Hybrid Programs......Page 212 Preliminaries on Lifted Inference......Page 220 LP......Page 227 Lifted Inference with Aggregation Parfactors......Page 230 Weighted First-Order Model Counting......Page 232 Comparison of the Approaches......Page 235 ProbLog1......Page 237 MCINTYRE......Page 242 Approximate Inference for Queries with infinite Number of Explanations......Page 245 Conditional Approximate Inference......Page 246 Approximate Inference by Sampling for Hybrid Programs......Page 247 Approximate Inference with Bounded Error for Hybrid Programs......Page 250 k-Optimal......Page 253 Explanation-based Approximate Weighted Model Counting......Page 255 Approximate Inference with Tp-Compilation......Page 257 DISTR & EXP Tasks......Page 258 Possibilistic Logic Programming......Page 263 Decision-Theoretic ProbLog......Page 265 Algebraic ProbLog......Page 274 PRISM Parameter Learning......Page 283 LLPAD & ALLPAD Parameter Learning......Page 289 LeProbLog......Page 291 EMBLEM......Page 294 ProbLog2 Parameter Learning......Page 304 Parameter Learning for Hybrid Programs......Page 306 Inductive Logic Programming......Page 307 LLPAD & ALLPAD Structure Learning......Page 311 ProbLog Theory Compression......Page 313 ProbFOIL & ProbFOIL+......Page 314 SLIPCOVER......Page 320 Examples of Datasets......Page 328 cplint Commands......Page 329 Natural Language Processing......Page 333 Drawing Binary Decision Diagrams......Page 337 Gaussian Processes......Page 338 Dirichlet Processes......Page 342 Bayesian Estimation......Page 350 Kalman Filter......Page 351 Stochastic Logic Programs......Page 354 Tile Map Generation......Page 356 Markov Logic Networks......Page 358 Truel......Page 359 Coupon Collector Problem......Page 363 1D Random Walk......Page 365 Latent Dirichlet Allocation......Page 366 Indian GPA Problem......Page 370 Bongard Problems......Page 372 Conclusions......Page 375 Refs......Page 377 Index......Page 399