LEADER 11145nam 2200529 450 001 9910590059503321 005 20230113143728.0 010 $a3-031-15707-9 035 $a(MiAaPQ)EBC7078231 035 $a(Au-PeEL)EBL7078231 035 $a(CKB)24750398000041 035 $a(PPN)264191528 035 $a(EXLCZ)9924750398000041 100 $a20230113d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aLogic programming and nonmonotonic reasoning $e16th international conference, LPNMR 2022, Genova, Italy, September 5-9, 2022, proceedings /$fGeorg Gottlob, Daniela Inclezan, Marco Maratea (editors) 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$dİ2022 215 $a1 online resource (536 pages) 225 1 $aLecture notes in computer science. Lecture notes in artificial intelligence ;$vVolume 13416 311 08$aPrint version: Gottlob, Georg Logic Programming and Nonmonotonic Reasoning Cham : Springer International Publishing AG,c2022 9783031157066 327 $aIntro -- Preface -- Organization -- Abstracts of Invited Talks -- DLV Evolution from Datalog to Ontology and Stream Reasoning -- Reward Machines: Formal Languages and Automata for Reinforcement Learning -- Logic-Based Machine Learning: Recent Advances and Their Role in Neuro-Symbolic AI -- Abstract Argumentation with Focus on Argument Claims - An Overview -- Contents -- Technical Contributions -- Syntactic ASP Forgetting with Forks -- 1 Introduction -- 2 Background -- 3 The Cut Operator -- 4 Forgetting into Forks: The Unfolding Operator -- 5 Conclusions -- References -- Modal Logic S5 in Answer Set Programming with Lazy Creation of Worlds -- 1 Introduction -- 2 Background -- 3 S5 Satisfiability Checking Encodings -- 4 Implementation in Answer Set Programming -- 5 Evaluation -- 6 Related Work -- 7 Conclusion -- References -- Enumeration of Minimal Models and MUSes in WASP -- 1 Introduction -- 2 Preliminaries -- 3 Enumeration of Minimal Stable Models -- 4 Enumeration of MUSes -- 5 Experiments -- 6 Related Work -- 7 Conclusions -- References -- Statistical Statements in Probabilistic Logic Programming -- 1 Introduction -- 2 Background -- 2.1 Answer Set Programming -- 2.2 Probabilistic Logic Programming -- 2.3 Credal Semantics -- 2.4 Probabilistic Conditionals -- 3 Probabilistic Answer Set Programming for Statistical Probabilities (PASTA) -- 4 Inference in PASTA -- 5 Experiments -- 6 Related Work -- 7 Conclusions -- References -- A Comparative Study of Three Neural-Symbolic Approaches to Inductive Logic Programming -- 1 Introduction -- 2 Studied Neural-Symbolic Algorithms for ILP -- 3 A Comparison Based on Four Characteristics -- 3.1 Representation of Data -- 3.2 Language Bias -- 3.3 Recursion -- 3.4 Predicate Invention -- 4 Open Challenges and Conclusion -- References -- A Definition of Sceptical Semantics in the Constellations Approach. 327 $a1 Introduction -- 2 The Constellations Approach -- 3 Related Work -- 4 The Grounded Semantics of a PrAF -- 5 Further Sceptical Semantics -- 6 Conclusions and Future Work -- References -- SHACL: A Description Logic in Disguise -- 1 Introduction -- 2 The Wedge -- 3 SHACL, OWL, and Description Logics -- 4 SHACL: The Logical Perspective -- 5 From Graphs to Interpretations -- 6 Related Work and Conclusion -- References -- Tunas - Fishing for Diverse Answer Sets: A Multi-shot Trade up Strategy -- 1 Introduction -- 2 Preliminaries -- 2.1 Multi-shot Answer Set Programming -- 2.2 Diverse Solutions -- 3 Iterative Reworking Strategies -- 3.1 Problem Definition and Complexity -- 3.2 Reworking Methods -- 4 Experimental Evaluation -- 5 Conclusion and Future Work -- References -- Emotional Reasoning in an Action Language for Emotion-Aware Planning -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 3.1 Emotion Theories: AE and HER -- 3.2 Action Reasoning and Transition Systems -- 4 Emotional Reasoning -- 4.1 Emotion Decision-Graph (EDG) -- 4.2 Action Language Specifications -- 4.3 Proving Safe Emotional Change -- 4.4 Example Scenario: Backward Reasoning -- 4.5 Example Scenario: Forward Reasoning -- 5 Discussion -- 6 Conclusion and Future Work -- References -- Metric Temporal Answer Set Programming over Timed Traces -- 1 Introduction -- 2 Metric Temporal Logic -- 3 Translation into Monadic Quantified Here-and-There with Difference Constraints -- 4 Discussion -- References -- Epistemic Logic Programs: A Study of Some Properties -- 1 Introduction -- 2 Answer Set Programming and Answer Set Semantics -- 3 Epistemic Logic Programs and Their Properties -- 4 Our Observations and Proposal -- 5 Discussion and Conclusions -- A Epistemic Logic Programs: Useful Properties -- References. 327 $aDeep Learning for the Generation of Heuristics in Answer Set Programming: A Case Study of Graph Coloring -- 1 Introduction -- 2 Background -- 2.1 Graph Coloring Problem -- 2.2 Stable Model Search -- 2.3 Deep Neural Networks -- 3 Generation of Domain-Specific Heuristics in ASP -- 3.1 Representation of ASP Instances -- 3.2 Generation of the Training Set -- 3.3 Generation of the Deep Learning Model -- 3.4 Integration of the Deep Learning Model in wasp -- 4 Experiment -- 5 Related Work -- 6 Conclusion -- References -- A Qualitative Temporal Extension of Here-and-There Logic -- 1 Introduction -- 2 Preliminaries -- 3 Qualitative Temporal Here-and-There Logic -- 4 Temporal Tableau Calculus -- 5 Prototypical Implementation -- 6 Related Work and Conclusion -- References -- Representing Abstract Dialectical Frameworks with Binary Decision Diagrams -- 1 Introduction -- 2 Background -- 3 Representing ADFs as BDDs -- 4 Search Space Exploitation: Profiting from BDDs -- 5 Preliminary Experiments -- 6 Conclusions -- References -- Arguing Correctness of ASP Programs with Aggregates -- 1 Introduction -- 2 Review: Logic Programs via the Many-Sorted Approach -- 2.1 Syntax of Logic Programs with Aggregates -- 2.2 From Rules to Many-Sorted First-Order Formulas -- 2.3 Semantics via the SM Operator -- 3 Proving the Correctness of Logic Programs -- 3.1 The Graph Coloring Problem -- 3.2 The Traveling Salesman Problem -- 4 Conclusions and Future Work -- References -- Efficient Computation of Answer Sets via SAT Modulo Acyclicity and Vertex Elimination -- 1 Introduction -- 2 Preliminaries -- 3 Translating ASP into SAT Modulo Graphs/Acyclicity -- 3.1 Normalization -- 3.2 Instrumentation with Acyclicity Constraint -- 3.3 Program Completion Modulo Acyclicity -- 4 Vertex Elimination -- 5 Translating SAT Modulo Acyclicity into Pure SAT -- 6 Translating ASP into Pure SAT. 327 $a7 Experimental Evaluation -- 8 Discussion and Conclusion -- References -- IASCAR: Incremental Answer Set Counting by Anytime Refinement -- 1 Introduction -- 2 Preliminaries -- 3 Counting Supported Models -- 3.1 Counting Supported Models Under Assumptions -- 3.2 Compressing Counting Graphs -- 4 Incremental Counting by Inclusion-Exclusion -- 5 Preliminary Empirical Evaluation -- 6 Conclusion and Future Work -- References -- Reasoning About Actions with EL Ontologies and Temporal Answer Sets for DLTL -- 1 Introduction -- 2 The Description Logic EL -- 3 Temporal Action Theories in DLTL and Temporal Answer Sets -- 4 Combining Temporal Action Theories with EL Ontologies -- 5 Ontology Axioms as State Constraints -- 6 Causal Laws for Repairing Inconsistencies: Sufficient Conditions -- 7 Conclusions and Related Work -- References -- Inference to the Stable Explanations -- 1 Introduction -- 2 The Logical Framework of Defeasible Logic -- 3 Computational Problem and Methodology -- 4 Complexity Results -- 5 Abduction and Theory Change -- 6 Related Work -- 7 Conclusions and Future Investigations -- References -- Semantics for Conditional Literals via the SM Operator -- 1 Introduction -- 2 Syntax of Conditional Programs -- 3 Semantics via the SM Operator -- 4 Semantics via Infinitary Propositional Logic -- 5 Connecting Two Semantics of Conditional Programs -- 6 Arguing Correctness of the K-Coloring Problem -- References -- State Transition in Multi-agent Epistemic Domains Using Answer Set Programming -- 1 Introduction -- 2 Preliminaries -- 3 State Transition Using ASP -- 4 Properties of the State Transition Function -- 5 Example Scenarios -- 6 Related Literature -- 7 Conclusion -- References -- Towards Provenance in Heterogeneous Knowledge Bases -- 1 Introduction -- 2 Provenance Semirings -- 3 Provenance Multi-context Systems -- 4 Grounded Equilibria. 327 $a5 Conclusions -- References -- Computing Smallest MUSes of Quantified Boolean Formulas -- 1 Introduction -- 2 Preliminaries -- 3 Smallest Strong Explanations -- 4 On Complexity of Computing Smallest MUSes of QBFs -- 5 Computing Smallest MUSes via Implicit Hitting Sets -- 6 Empirical Evaluation -- 7 Conclusions -- References -- Pinpointing Axioms in Ontologies via ASP -- 1 Introduction -- 2 Preliminaries -- 3 Reasoning Through Rules -- 4 Axiom Pinpointing Through ASP -- 5 Conclusions -- References -- Interlinking Logic Programs and Argumentation Frameworks -- 1 Introduction -- 2 Preliminaries -- 3 Linking LP and AF -- 3.1 From AF to LP -- 3.2 From LP to AF -- 3.3 Bidirectional Framework -- 4 Applications -- 4.1 Deductive Argumentation -- 4.2 Argument Aggregation -- 4.3 Multi-context System -- 4.4 Constrained Argumentation Frameworks -- 5 Complexity -- 6 Concluding Remarks -- References -- Gradient-Based Supported Model Computation in Vector Spaces -- 1 Introduction -- 2 Background -- 3 Representing Logic Programs with Matrices -- 3.1 Relationship Between Positive Forms and Supported Models -- 3.2 Matrix Encoding of Logic Programs -- 4 Gradient Descent for Computing Supported Models -- 4.1 Computing the TP Operator in Vector Spaces -- 4.2 Loss Function for Computing Supported Models -- 5 Experiments -- 5.1 N-negative Loops -- 5.2 Choose 1 Out of N -- 5.3 Random Programs -- 6 Conclusion -- References -- Towards Causality-Based Conflict Resolution in Answer Set Programs -- 1 Introduction -- 2 Preliminaries -- 3 Causality-Based Conflict Resolution -- 3.1 Conflicts and Inconsistency -- 3.2 Conflict Resolution -- 4 Strategies for Conflict Resolution -- 4.1 General Satisfaction Interdependencies -- 4.2 Blocking Rules Using Opposing Rules -- 4.3 Relevant Rule Modification -- 5 Related Work -- 6 Conclusion and Future Work -- References. 327 $axASP: An Explanation Generation System for Answer Set Programming. 410 0$aLecture notes in computer science. 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