Handbook of knowledge representation

Handbook of knowledge representation

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Weitere Verfasser: Harmelen, Frank van (HerausgeberIn)
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Sprache:English
Veröffentlicht: Amsterdam [u.a.] Elsevier 2008
Ausgabe:1. ed.
Schriftenreihe:Foundations of artificial intelligence
Schlagworte:
Inteligência artificial
Representação de conhecimento
Représentation des connaissances
Knowledge representation (Information theory)
Informationstheorie
Wissensrepräsentation
Künstliche Intelligenz
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adam_text Contents Dedication v Preface vii Editors xi Contributors xiii Contents xv I General Methods in Knowledge Representation and Reasoning 1 1 Knowledge Representation and Classical Logic 3 Vladimir Lifschitz, Leora Morgenstern and David Plaisted 1.1 Knowledge Representation and Classical Logic ............ 3 1.2 Syntax, Semantics and Natural Deduction ............... 4 1.2.1 Propositional Logic ....................... 4 1.2.2 First-Order Logic ........................ 8 1.2.3 Second-Order Logic ....................... 16 1.3 Automated Theorem Proving ...................... 18 1.3.1 Resolution in the Propositional Calculus ............ 22 1.3.2 First-Order Proof Systems ................... 25 1.3.3 Equality ............................. 37 1.3.4 Term Rewriting Systems .................... 43 1.3.5 Confluence and Termination Properties ............ 46 1.3.6 Equational Rewriting ...................... 50 1.3.7 Other Logics ........................... 55 1.4 Applications of Automated Theorem Provers ............. 58 1.4.1 Applications Involving Human Intervention .......... 59 1.4.2 Non-Interactive KR Applications of Automated Theorem Provers .............................. 61 1.4.3 Exploiting Structure ....................... 64 1.4.4 Prolog .............................. 65 1.5 Suitability of Logic for Knowledge Representation .......... 67 1.5.1 Anti-logicist Arguments and Responses ............ 67 xv xvi Contents Acknowledgements .............................. 74 Bibliography .................................. 74 2 Satisfiability Solvers 89 Carla P. Gomes, Henry Kautz, Ashish Sabharwal and Bart Selmán 2.1 Definitions and Notation ........................ 91 2.2 SAT Solver Technology—Complete Methods ............. 92 2.2.1 The DPLL Procedure ...................... 92 2.2.2 Key Features of Modern DPLL-Based SAT Solvers ..... 93 2.2.3 Clause Learning and Iterative DPLL .............. 95 2.2.4 A Proof Complexity Perspective ................ 100 2.2.5 Symmetry Breaking ....................... 104 2.3 SAT Solver Technology—Incomplete Methods ............ 107 2.3.1 The Phase Transition Phenomenon in Random fc-SAT .... 109 2.3.2 A New Technique for Random ł-SAT: Survey Propagation . Ill 2.4 Runtime Variance and Problem Structure ............... 112 2.4.1 Fat and Heavy Tailed Behavior ................. 113 2.4.2 Backdoors ............................ 113 2.4.3 Restarts .............................. 115 2.5 Beyond SAT: Quantified Boolean Formulas and Model Counting . . 117 2.5.1 QBFReasoning ......................... 117 2.5.2 Model Counting ......................... 120 Bibliography .................................. 122 3 Description Logics 135 Franz Baader, Ian Horrocks and Ulrike Sattler 3.1 Introduction ............................... 135 3.2 A Basic DL and its Extensions ..................... 139 3.2.1 Syntax and Semantics of ЛСС ................. 140 3.2.2 Important Inference Problems ................. 141 3.2.3 Important Extensions to ЛСС ................. 142 3.3 Relationships with other Formalisms .................. 144 3.3.1 DLs and Predicate Logic .................... 144 3.3.2 DLs and Modal Logic ...................... 145 3.4 Tableau Based Reasoning Techniques ................. 146 3.4.1 A Tableau Algorithm for ЛСС ................. 146 3.4.2 Implementation and Optimization Techniques ........ 150 3.5 Complexity ................................ 151 3.5.1 ЛСС АВох Consistency is PSpace-complete ......... 151 3.5.2 Adding General TBoxes Results in ExpTime-Hardness ... 154 3.5.3 The Effect of other Constructors ................ 154 3.6 Other Reasoning Techniques ...................... 155 3.6.1 The Automata Based Approach ................ 156 3.6.2 Structural Approaches ...................... 161 3.7 DLs in Ontology Language Applications ............... 166 3.7.1 The OWL Ontology Language ................. 166 3.7.2 OWL Tools and Applications .................. 167 Contents xvii 3.8 Further Reading ............................. 168 Bibliography .................................. 169 Constraint Programming 181 Francesca Rossi, Peter van Beek and Toby Walsh 4.1 Introduction ............................... 181 4.2 Constraint Propagation ......................... 182 4.2.1 Local Consistency ........................ 183 4.2.2 Global Constraints ........................ 183 4.3 Search .................................. 184 4.3.1 Backtracking Search ...................... 184 4.3.2 Local Search ........................... 187 4.3.3 Hybrid Methods ......................... 188 4.4 Tractability ................................ 189 4.4.1 Tractable Constraint Languages ................ 189 4.4.2 Tractable Constraint Graphs .................. 191 4.5 Modeling ................................. 191 4.5.1 CP v - CP ............................ 192 4.5.2 Viewpoints ............................ 192 4.5.3 Symmetry ............................ 193 4.6 Soft Constraints and Optimization ................... 193 4.6.1 Modeling Soft Constraints ................... 194 4.6.2 Searching for the Best Solution ................. 195 4.6.3 Inference in Soft Constraints .................. 195 4.7 Constraint Logic Programming ..................... 197 4.7.1 Logic Programs ......................... 197 4.7.2 Constraint Logic Programs ................... 198 4.7.3 LP and CLP Languages ..................... 198 4.7.4 Other Programming Paradigms ................. 199 4.8 Beyond Finite Domains ......................... 199 4.8.1 Intervals ............................. 199 4.8.2 Temporal Problems ....................... 200 4.8.3 Sets and other Datatypes .................... 200 4.9 Distributed Constraint Programming .................. 201 4.10 Application Areas ............................ 202 4.11 Conclusions ............................... 203 Bibliography .................................. 203 Conceptual Graphs 213 John F. Sowa 5.1 From Existential Graphs to Conceptual Graphs ............ 213 5.2 Common Logic ............................. 217 5.3 Reasoning with Graphs ......................... 223 5.4 Propositions, Situations, and Metalanguage .............. 230 5.5 Research Extensions ........................... 233 Bibliography .................................. 235 xviii Contents 6 Nonmonotonic Reasoning 239 Gerhard Brewka, Ilkka Memela and Mirosław Truszczyński 6.1 Introduction ............................... 239 Rules with exceptions .......................... 240 The frame problem ........................... 240 About this chapter ............................ 241 6.2 Default Logic .............................. 242 6.2.1 Basic Definitions and Properties ................ 242 6.2.2 Computational Properties .................... 246 6.2.3 Normal Default Theories .................... 249 6.2.4 Closed-World Assumption and Normal Defaults ....... 250 6.2.5 Variants of Default Logic .................... 252 6.3 Autoepistemic Logic ........................... 252 6.3.1 Preliminaries, Intuitions and Basic Results .......... 253 6.3.2 Computational Properties .................... 258 6.4 Circumscription ............................. 260 6.4.1 Motivation ............................ 260 6.4.2 Defining Circumscription .................... 261 6.4.3 Semantics ............................ 263 6.4.4 Computational Properties .................... 264 6.4.5 Variants .............................. 266 6.5 Nonmonotonic Inference Relations ................... 267 6.5.1 Semantic Specification of Inference Relations ......... 268 6.5.2 Default Conditionals ...................... 270 6.5.3 Discussion ............................ 272 6.6 Further Issues and Conclusion ..................... 272 6.6.1 Relating Default and Autoepistemic Logics .......... 273 6.6.2 Relating Default Logic and Circumscription ......... 275 6.6.3 Further Approaches ....................... 276 Acknowledgements .............................. 277 Bibliography .................................. 277 7 Answer Sets 285 Michael Gelfond 7.1 Introduction ............................... 285 7.2 Syntax and Semantics of Answer Set Prolog .............. 286 7.3 Properties of Logic Programs ...................... 292 7.3.1 Consistency of Logic Programs ................ 292 7.3.2 Reasoning Methods for Answer Set Prolog .......... 295 7.3.3 Properties of Entailment .................... 297 7.3.4 Relations between Programs .................. 298 7.4 A Simple Knowledge Base ....................... 300 7.5 Reasoning in Dynamic Domains .................... 302 7.6 Extensions of Answer Set Prolog .................... 307 7.7 Conclusion ................................ 309 Acknowledgements .............................. 310 Bibliography .................................. 310 Contents xix 8 Belief Revision 317 Pavios Peppas 8.1 Introduction ............................... 317 8.2 Preliminaries ............................... 318 8.3 The AGM Paradigm ........................... 318 8.3.1 The AGM Postulates for Belief Revision ........... 319 8.3.2 The AGM Postulates for Belief Contraction .......... 320 8.3.3 Selection Functions ....................... 323 8.3.4 Epistemic Entrenchment .................... 325 8.3.5 System of Spheres ........................ 327 8.4 Belief Base Change ........................... 329 8.4.1 Belief Base Change Operations ................. 331 8.4.2 Belief Base Change Schemes .................. 332 8.5 Multiple Belief Change ......................... 335 8.5.1 Multiple Revision ........................ 336 8.5.2 Multiple Contraction ...................... 338 8.6 Iterated Revision ............................. 340 8.6.1 Iterated Revision with Enriched Epistemic Input ....... 340 8.6.2 Iterated Revision with Simple Epistemic Input ........ 343 8.7 Non-Prioritized Revision ........................ 346 8.8 BeliefUpdate .............................. 349 8.9 Conclusion ................................ 352 Acknowledgements .............................. 353 Bibliography .................................. 353 9 Qualitative Modeling 361 Kenneth D. Forbus 9.1 Introduction ............................... 361 9.1.1 Key Principles .......................... 362 9.1.2 Overview of Basic Qualitative Reasoning ........... 363 9.2 Qualitative Mathematics ......................... 365 9.2.1 Quantities ............................ 365 9.2.2 Functions and Relationships .................. 369 9.3 Ontology ................................. 371 9.3.1 Component Ontologies ..................... 372 9.3.2 Process Ontologies ....................... 373 9.3.3 Field Ontologies ......................... 374 9.4 Causality ................................. 374 9.5 Compositional Modeling ........................ 376 9.5.1 Model Formulation Algorithms ................. 378 9.6 Qualitative States and Qualitative Simulation ............. 379 9.7 Qualitative Spatial Reasoning ...................... 381 9.7.1 Topological Representations .................. 381 9.7.2 Shape, Location, and Orientation Representations ...... 382 9.7.3 Diagrammatic Reasoning .................... 382 9.8 Qualitative Modeling Applications ................... 383 xx Contents 9.8.1 Automating or Assisting Professional Reasoning ....... 383 9.8.2 Education ............................ 384 9.8.3 Cognitive Modeling ....................... 386 9.9 Frontiers and Resources ......................... 387 Bibliography .................................. 387 10 Model-based Problem Solving 395 Peter Struss 10.1 Introduction .............................. 395 10.2 Tasks .................................. 398 10.2.1 Situation Assessment/Diagnosis .............. 398 10.2.2 Test Generation, Measurement Proposal, Diagnosability Analysis ........................... 399 10.2.3 Design and Failure-Modes-and-Effects Analysis ..... 401 10.2.4 Proposal of Remedial Actions (Repair, Reconfiguration, Recovery, Therapy) ..................... 402 10.2.5 Ingredients of Model-based Problem Solving ....... 402 10.3 Requirements on Modeling ...................... 403 10.3.1 Behavior Prediction and Consistency Check ....... 404 10.3.2 Validity of Behavior Modeling ............... 405 10.3.3 Conceptual Modeling .................... 405 10.3.4 (Automated) Model Composition ............. 406 10.3.5 Genericky .......................... 406 10.3.6 Appropriate Granularity .................. 407 10.4 Diagnosis ............................... 407 10.4.1 Consistency-based Diagnosis with Component-oriented Models ............................ 408 10.4.2 Computation of Diagnoses ................. 418 10.4.3 Solution Scope and Limitations of Component-Oriented Diagnosis .......................... 422 10.4.4 Diagnosis across Time ................... 423 10.4.5 Abductive Diagnosis .................... 431 10.4.6 Process-Oriented Diagnosis ................ 434 10.4.7 Model-based Diagnosis in Control Engineering ...... 438 10.5 Test and Measurement Proposal, Diagnosability Analysis ..... 438 10.5.1 Test Generation ....................... 439 10.5.2 Entropy-based Test Selection ................ 444 10.5.3 Probe Selection ....................... 445 10.5.4 Diagnosability Analysis ................... 446 10.6 Remedy Proposal ........................... 446 10.6.1 Integration of Diagnosis and Remedy Actions ...... 448 10.6.2 Component-oriented Reconfiguration ........... 450 10.6.3 Process-oriented Therapy Proposal ............ 453 10.7 Other Tasks .............................. 454 10.7.1 Configuration and Design .................. 454 10.7.2 Failure-Modes-and-Effects Analysis ............ 456 10.7.3 Debugging and Testing of Software ............ 456 Contents xxi 10.8 State and Challenges ......................... 458 Acknowledgements .............................. 460 Bibliography ................................. 460 11 Bayesian Networks 467 Adnan Darwiche 11.1 Introduction .............................. 467 11.2 Syntax and Semantics of Bayesian Networks ............ 468 11.2.1 Notational Conventions ................... 468 11.2.2 Probabilistic Beliefs ..................... 469 11.2.3 Bayesian Networks ..................... 470 11.2.4 Structured Representations of CPTs ............ 471 11.2.5 Reasoning about Independence ............... 471 11.2.6 Dynamic Bayesian Networks ................ 472 11.3 Exact Inference ............................ 473 11.3.1 Structure-Based Algorithms ................ 474 11.3.2 Inference with Local (Parametric) Structure ........ 479 11.3.3 Solving MAP and МРЕ by Search ............. 480 11.3.4 Compiling Bayesian Networks ............... 481 11.3.5 Inference by Reduction to Logic .............. 482 11.3.6 Additionallnference Techniques .............. 484 11.4 Approximate Inference ........................ 485 11.4.1 Inference by Stochastic Sampling ............. 485 11.4.2 Inference as Optimization ................. 486 11.5 Constructing Bayesian Networks .................. 489 11.5.1 Knowledge Engineering .................. 489 11.5.2 High-Level Specifications ................. 490 11.5.3 Learning Bayesian Networks ................ 493 11.6 Causality and Intervention ...................... 497 Acknowledgements .............................. 498 Bibliography ................................. 499 11 Classes of Knowledge and Specialized Representations 511 12 Temporal Representation and Reasoning 513 Michael Fisher 12.1 Temporal Structures .......................... 514 12.1.1 Instants and Durations ................... 514 12.1.2 From Discreteness to Density ............... 515 12.1.3 Granularity Hierarchies ................... 516 12.1.4 Temporal Organisation ................... 517 12.1.5 Moving in Real Time .................... 517 12.1.6 Intervals ........................... 518 12.2 Temporal Language .......................... 520 12.2.1 Modal Temporal Logic ................... 520 12.2.2 Back to the Future ...................... 521 12.2.3 Temporal Arguments and Reified Temporal Logics . . . . 521 xxii Contents 12.2.4 Operators over Non-discrete Models............ 522 12.2.5 Intervals ........................... 523 12.2.6 Real-Time and Hybrid Temporal Languages ....... 524 12.2.7 Quantification ........................ 525 12.2.8 Hybrid Temporal Logic and the Concept of now .... 528 12.3 Temporal Reasoning ......................... 528 12.3.1 Proof Systems ........................ 529 12.3.2 Automated Deduction .................... 529 12.4 Applications .............................. 530 12.4.1 Natural Language ...................... 530 12.4.2 Reactive System Specification ............... 531 12.4.3 Theorem-Proving ...................... 532 12.4.4 Model Checking ....................... 532 12.4.5 PSL/Sugar .......................... 534 12.4.6 Temporal Description Logics ................ 534 12.5 Concluding Remarks ......................... 535 Acknowledgements .............................. 535 Bibliography ................................. 535 13 Qualitative Spatial Representation and Reasoning 551 Anthony G. Cohn and Jochen Renz 13.1 Introduction .............................. 551 13.1.1 What is Qualitative Spatial Reasoning? .......... 551 13.1.2 Applications of Qualitative Spatial Reasoning ...... 553 13.2 Aspects of Qualitative Spatial Representation ............ 554 13.2.1 Ontology ........................... 554 13.2.2 Spatial Relations ...................... 556 13.2.3 Mereology .......................... 557 13.2.4 Mereotopology ....................... 557 13.2.5 Between Mereotopology and Fully Metric Spatial Repre¬ sentation ........................... 566 13.2.6 Mereogeometry ....................... 570 13.2.7 Spatial Vagueness ...................... 571 13.3 Spatial Reasoning ........................... 572 13.3.1 Deduction .......................... 574 13.3.2 Composition ......................... 575 13.3.3 Constraint-based Spatial Reasoning ............ 576 13.3.4 Finding Efficient Reasoning Algorithms .......... 578 13.3.5 Planar Realizability ..................... 581 13.4 Reasoning about Spatial Change ................... 581 13.5 Cognitive Validity ........................... 582 13.6 Final Remarks ............................. 583 Acknowledgements .............................. 584 Bibliography ................................. 584 Contents xxiii 14 Physical Reasoning 597 Ernest Davis 14.1 Architectures ............................. 600 14.1.1 Component Analysis .................... 600 14.1.2 Process Model ........................ 601 14.2 Domain Theories ........................... 602 14.2.1 Rigid Object Kinematics .................. 603 14.2.2 Rigid Object Dynamics ................... 605 14.2.3 Liquids ............................ 608 14.3 Abstraction and Multiple Models .................. 611 14.4 Historical and Bibliographical .................... 614 14.4.1 Logic-based Representations ................ 614 14.4.2 Solid Objects: Kinematics ................. 615 14.4.3 Solid Object Dynamics ................... 616 14.4.4 Abstraction and Multiple Models ............. 616 14.4.5 Other ............................. 616 14.4.6 Books ............................ 617 Bibliography ................................. 618 15 Reasoning about Knowledge and Belief 621 Yoram Moses 15.1 Introduction .............................. 621 15.2 The Possible Worlds Model ..................... 622 15.2.1 A Language for Knowledge and Belief .......... 622 15.3 Properties of Knowledge ....................... 626 15.4 The Knowledge of Groups ...................... 628 15.4.1 Common Knowledge .................... 629 15.4.2 Distributed Knowledge ................... 632 15.5 Runs and Systems ........................... 633 15.6 Adding Time ............................. 635 15.6.1 Common Knowledge and Time .............. 636 15.7 Knowledge-based Behaviors ..................... 637 15.7.1 Contexts and Protocols ................... 637 15.7.2 Knowledge-based Programs ................ 639 15.7.3 A Subtle kb Program .................... 641 15.8 Beyond Square One .......................... 643 15.9 How to Reason about Knowledge and Belief ............ 644 15.9.1 Concluding Remark ..................... 645 Bibliography ................................. 645 Further reading ................................ 647 16 Situation Calculus 649 Fangzhen Lin 16.1 Axiomatizations ............................ 650 16.2 The Frame, the Ramification and the Qualification Problems . . . 652 16.2.1 The Frame Problem—Reiter s Solution .......... 654 16.2.2 The Ramification Problem and Lin s Solution ....... 657 xxiv Contents 16.2.3 The Qualification Problem................. 660 16.3 Reiter s Foundational Axioms and Basic Action Theories ..... 661 16.4 Applications .............................. 665 16.5 Concluding Remarks ......................... 667 Acknowledgements .............................. 667 Bibliography ................................. 667 17 Event Calculus 671 Erik T. Mueller 17.1 Introduction .............................. 671 17.2 Versions of the Event Calculus .................... 672 17.2.1 Original Event Calculus (OEC) .............. 672 17.2.2 Simplified Event Calculus (SEC) .............. 674 17.2.3 Basic Event Calculus (ВЕС) ................ 676 17.2.4 Event Calculus (EC) .................... 679 17.2.5 Discrete Event Calculus (DEC) .............. 681 17.2.6 Equivalence of DEC and EC ................ 683 17.2.7 Other Versions ........................ 683 17.3 Relationship to other Formalisms .................. 684 17.4 Default Reasoning .......................... 684 17.4.1 Circumscription ....................... 684 17.4.2 Computing Circumscription ................ 685 17.4.3 Historical Note ....................... 686 17.4.4 Negation as Failure ..................... 687 17.5 Event Calculus Knowledge Representation ............. 687 17.5.1 Parameters .......................... 687 17.5.2 Event Effects ........................ 688 17.5.3 Preconditions ........................ 689 17.5.4 State Constraints ...................... 689 17.5.5 Concurrent Events ...................... 690 17.5.6 Triggered Events ...................... 691 17.5.7 Continuous Change ..................... 692 17.5.8 Nondeterministic Effects .................. 693 17.5.9 Indirect Effects ....................... 694 17.5.10 Partially Ordered Events .................. 696 17.6 Action Language 8.......................... 697 17.7 Automated Event Calculus Reasoning ................ 699 17.7.1 Prolog ............................ 699 17.7.2 Answer Set Programming ................. 700 17.7.3 Satisfiability (SAT) Solving ................ 700 17.7.4 First-Order Logic Automated Theorem Proving ..... 700 17.8 Applications of the Event Calculus ................. 700 Bibliography ................................. 701 18 Temporal Action Logics 709 Patrick Doherty and Jonas Kvarnström 18.1 Introduction .............................. 709 Contents xxv 18.1.1 PMONandTAL...................... 710 18.1.2 Previous Work ....................... 711 18.1.3 Chapter Structure ..................... 713 18.2 Basic Concepts ............................ 713 18.3 TAL Narratives ............................ 716 18.3.1 The Russian Airplane Hijack Scenario .......... 717 18.3.2 Narrative Background Specification ........... 718 18.3.3 Narrative Specification .................. 723 18.4 The Relation Between the TAL Languages £(ND) and £(FL) . . 724 18.5 The TAL Surface Language £(ND) ................. 725 18.5.1 Sorts, Terms and Variables ................ 725 18.5.2 Formulas .......................... 726 18.5.3 Statements ......................... 727 18.6 The TAL Base Language £(FL) ................... 728 18.6.1 Translation from £(ND) to £(FL) ............ 728 18.7 Circumscription and TAL ....................... 730 18.8 Representing Ramifications in TAL ................. 735 18.9 Representing Qualifications in TAL ................. 737 18.9.1 Enabling Fluents ...................... 738 18.9.2 Strong Qualification .................... 740 18.9.3 Weak Qualification ..................... 740 18.9.4 Qualification: Not Only For Actions ........... 741 18.9.5 Ramifications as Qualifications .............. 742 18.10 Action Expressivity in TAL ..................... 742 18.11 Concurrent Actions in TAL ...................... 744 18.11.1 Independent Concurrent Actions ............. 744 18.11.2 Interacting Concurrent Actions .............. 745 18.11.3 Laws of Interaction .................... 745 18.12 An Application of TAL: TALplanner ................ 747 18.13 Summary ............................... 752 Acknowledgements .............................. 752 Bibliography ................................. 753 19 Nonmonotonic Causal Logic 759 Hudson Türner 19.1 Fundamentals ............................. 762 19.1.1 Finite Domain Propositional Logic ............ 762 19.1.2 Causal Theories ...................... 763 19.2 Strong Equivalence .......................... 765 19.3 Completion .............................. 766 19.4 Expressiveness ............................ 768 19.4.1 Nondeterminism: Coin Tossing .............. 768 19.4.2 Implied Action Preconditions: Moving an Object .... 768 19.4.3 Things that Change by Themselves: Falling Dominos . 769 19.4.4 Things that Tend to Change by Themselves: Pendulum . 769 19.5 High-Level Action Language C+ .................. 770 19.6 Relationship to Default Logic .................... 771 xxvi Contents 19.7 Causal Theories in Higher-Order Classical Logic .......... 772 19.8 A Logic of Universal Causation ................... 773 Acknowledgement .............................. 774 Bibliography ................................. 774 III Knowledge Representation in Applications 777 20 Knowledge Representation and Question Answering 779 Marcello Balduccini, Chitta Barai and Yuliya Lierler 20.1 Introduction .............................. 779 20.1.1 Role of Knowledge Representation and Reasoning in QA 780 20.1.2 Architectural Overview of QA Systems Using Knowl¬ edge Representation and Reasoning ........... 782 20.2 From English to Logical Theories .................. 783 20.3 The COGEX Logic Prover of the LCC QA System ........ 790 20.4 Extracting Relevant Facts from Logical Theories and its Use in the DD QA System about Dynamic Domains and Trips ........ 792 20.4.1 The Overall Architecture of the DD System ....... 793 20.4.2 From Logic Forms to QSR Facts: An Illustration .... 794 20.4.3 OSR: From QSR Relations to Domain Relations .... 796 20.4.4 An Early Travel Module of the DD System ....... 798 20.4.5 Other Enhancements to the Travel Module ........ 802 20.5 From Natural Language to Relevant Facts in the ASU QA System 803 20.6 Nutcracker — System for Recognizing Textual Entailment ..... 806 20.7 Mueller s Story Understanding System ............... 810 20.8 Conclusion ............................... 813 Acknowledgements .............................. 815 Bibliography ................................. 815 21 The Semantic Web: Webizing Knowledge Representation 821 Jim Hendler and Frank van Harmelen 21.1 Introduction .............................. 821 21.2 The Semantic Web Today ...................... 823 21.3 Semantic Web KR Language Design ................ 826 21.3.1 Web Infrastructure ..................... 826 21.3.2 Webizing KR ........................ 827 21.3.3 Scalability and the Semantic Web ............ 830 21.4 OWL—Defining a Semantic Web KR Language .......... 831 21.5 Semantic Web KR Challenges .................... 836 21.6 Beyond OWL ............................. 836 21.7 Conclusion ............................... 837 Acknowledgements .............................. 837 Bibliography ................................. 838 22 Automated Planning 841 Alessandro Cimatti, Marco Pistore and Paolo Traverso 22.1 Introduction .............................. 841 Contents xxvii 22.2 The General Framework....................... 843 22.2.1 Domains.......................... 843 22.2.2 Plans and Plan Executions ................. 844 22.2.3 Goals and Problems.................... 845 22.3 Strong Planning under Full Observability .............. 845 22.4 Strong Cyclic Planning under Full Observability .......... 847 22.5 Planning for Temporally Extended Goals under Full Observability 850 22.6 Conformant Planning ......................... 857 22.7 Strong Planning under Partial Observability ............ 859 22.8 A Technological Overview ...................... 860 22.9 Conclusions .............................. 863 Bibliography ................................. 864 23 Cognitive Robotics 869 Hector Levesque and Gerhard Lakemeyer 23.1 Introduction .............................. 869 23.2 Knowledge Representation for Cognitive Robots .......... 870 23.2.1 Varieties of Actions .................... 871 23.2.2 Sensing ........................... 871 23.2.3 Knowledge ......................... 872 23.3 Reasoning for Cognitive Robots ................... 873 23.3.1 Projection via Progression and Regression ........ 873 23.3.2 Reasoning in Closed and Open Worlds .......... 875 23.4 High-Level Control for Cognitive Robots .............. 876 23.4.1 Classical Planning ..................... 876 23.4.2 High-Level Offline Robot Programming ......... 877 23.4.3 High-Level Online Robot Programming ......... 879 23.5 Conclusion ............................... 881 Bibliography ................................. 882 24 Multi-Agent Systems 887 Wiebe van der Hoek and Michael Wooldridge 24.1 Introduction .............................. 887 24.2 Representing Rational Cognitive States ............... 888 24.2.1 A Logical Toolkit ..................... 890 24.2.2 Dynamic Epistemic Logic ................. 891 24.2.3 Cohen and Levesque s Intention Logic .......... 893 24.2.4 Rao and Georgeff s BDI Logics .............. 896 24.2.5 The KARO Framework .................. 899 24.2.6 Discussion ......................... 903 24.2.7 Cognitive Agent Logics in Practice ............ 903 24.3 Representing the Strategic Structure of a System .......... 909 24.3.1 Coalition Logic ...................... 910 24.3.2 Strategic Temporal Logic: ATL .............. 913 24.3.3 Knowledge in Strategic Temporal Logics: ATEL ..... 916 24.3.4 CL-PC ........................... 919 24.3.5 Applications of Strategic Cooperation Logics ...... 920 xxviii Contents 24.4 Conclusions .............................. 920 Bibliography ................................. 920 25 Knowledge Engineering 929 Guus Schreiber 25.1 Introduction .............................. 929 25.2 Baseline ................................ 929 25.3 Tasks and Problem-Solving Methods ................ 930 25.3.1 Two Sample Problem-Solving Methods ......... 930 25.3.2 The Notion of Knowledge Role ............ 934 25.3.3 Specification Languages .................. 935 25.4 Ontologies ............................... 936 25.4.1 Ontology Specification Languages ............ 937 25.4.2 Types of Ontologies .................... 938 25.4.3 Ontology Engineering ................... 940 25.4.4 Ontologies and Data Models ............... 941 25.5 Knowledge Elicitation Techniques1 ................. 941 Bibliography ................................. 943 Author Index 947 Subject Index 987
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series2 Foundations of artificial intelligence
spellingShingle Handbook of knowledge representation
Inteligência artificial larpcal
Representação de conhecimento larpcal
Représentation des connaissances
Knowledge representation (Information theory)
Informationstheorie (DE-588)4026927-9 gnd
Wissensrepräsentation (DE-588)4049534-6 gnd
Künstliche Intelligenz (DE-588)4033447-8 gnd
subject_GND (DE-588)4026927-9
(DE-588)4049534-6
(DE-588)4033447-8
(DE-588)4143413-4
title Handbook of knowledge representation
title_auth Handbook of knowledge representation
title_exact_search Handbook of knowledge representation
title_full Handbook of knowledge representation ed. by Frank van Harmelen ...
title_fullStr Handbook of knowledge representation ed. by Frank van Harmelen ...
title_full_unstemmed Handbook of knowledge representation ed. by Frank van Harmelen ...
title_short Handbook of knowledge representation
title_sort handbook of knowledge representation
topic Inteligência artificial larpcal
Representação de conhecimento larpcal
Représentation des connaissances
Knowledge representation (Information theory)
Informationstheorie (DE-588)4026927-9 gnd
Wissensrepräsentation (DE-588)4049534-6 gnd
Künstliche Intelligenz (DE-588)4033447-8 gnd
topic_facet Inteligência artificial
Representação de conhecimento
Représentation des connaissances
Knowledge representation (Information theory)
Informationstheorie
Wissensrepräsentation
Künstliche Intelligenz
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