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Logic-Based Artificial Intelligence Book

Logic-Based Artificial Intelligence
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Logic-Based Artificial Intelligence, This landmark volume represents the culmination of over 40 years of research in the use of logic as a basis for representing and manipulating problems in the field of artificial intelligence. The use of logic as a basis for commonsense reasoning was start, Logic-Based Artificial Intelligence
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  • Logic-Based Artificial Intelligence
  • Written by author Jack Minker
  • Published by Springer-Verlag New York, LLC, 4/30/2013
  • This landmark volume represents the culmination of over 40 years of research in the use of logic as a basis for representing and manipulating problems in the field of artificial intelligence. The use of logic as a basis for commonsense reasoning was start
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Contributing Authors. Preface. Part I: Introduction to Logic-Based Artificial Intelligence. 1. Introduction to Logic-Based Artificial Intelligence; J. Minker. Part II: Commonsense Reasoning. 2. Concepts of Logical AI; J. McCarthy. Part III: Knowledge Representation. 3. Two Approaches to Efficient Open-World Reasoning; G. De Giacomo, H. Levesque. 4. Declarative Problem-Solving in DLV; T. Eder, et al. Part IV: Nonmonotonic Reasoning. 5. The Role of Default Logic in Knowledge Representation; J.P. Delgrande, Torsten Schaub. 6. Approximations, stable operators, well-founded fixpoints, applications in nonmonotonic reasoning; M. Denecker, et al. Part V: Logic for Causation, Actions. 7. Getting to the Airport: The Oldest Planning Problem in AI; V. Lifschitz, et al. Part VI: Planning, Problem Solving. 8. Encoding Domain Knowledge for Propositional Planning; H. Kautz, B. Selman. 9. Functional Strips; H. Geffner. Part VII: Logic, Planning, High Level Robotics. 10. Planning with Natural Actions in the Situation Calculus; F. Pirri, R. Reiter. 11. Reinventing Shakey; M. Shanahan. Part VIII: Logic for Agents, Actions. 12. Reasoning Agents in Dynamic Domains; C. Baral, M. Gelfond. 13. Dynamic Logic for Reasoning about Actions, Agents; J.-J.Ch. Meyer. Part IX: Inductive Reasoning. 14. Logic-Based Machine Learning; S. Muggleton, F. Marginean. Part X: Possibilistic Logic. 15. Decision, Nonmonotonic Reasoning, Possibilistic Logic; S. Benferhat, et al. Part Xl: Logic, Beliefs. 16. The Role(s) of Belief in AI; D. Perlis. 17. Modeling the Beliefs of Other Agents; R.H. Thomason. Part XII: Logic, Language. 18. The Situations We Talk about; L.K. Schuberi. Part XIII: Computational Logic. 19. Linear Time Datalog, Branching.Time Logic; G. Goitlob, et al. 20. On the Expressive Power of Planning Formalisms; B. Nebel. Part XIV: Knowledge Base System Implementations. 21. Extending the Smodels System with Cardinality, Weight Constraints; I. Niemelä, P. Simons. 22. Nonmonotonic Reasoning in LDL++; H. Wang, C. Zaniolo. Part XV: Applications of Theorem Proving, Logic Programming. 23. Towards a Mechanically Checked Theory of Computation; J. Strother Moore. 24. Logic-Based Techniques in Data Integration; A.Y. Levy. Index.


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Logic-Based Artificial Intelligence, This landmark volume represents the culmination of over 40 years of research in the use of logic as a basis for representing and manipulating problems in the field of artificial intelligence. The use of logic as a basis for commonsense reasoning was start, Logic-Based Artificial Intelligence

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Logic-Based Artificial Intelligence, This landmark volume represents the culmination of over 40 years of research in the use of logic as a basis for representing and manipulating problems in the field of artificial intelligence. The use of logic as a basis for commonsense reasoning was start, Logic-Based Artificial Intelligence

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Logic-Based Artificial Intelligence, This landmark volume represents the culmination of over 40 years of research in the use of logic as a basis for representing and manipulating problems in the field of artificial intelligence. The use of logic as a basis for commonsense reasoning was start, Logic-Based Artificial Intelligence

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