'Propositional logic' diaporamas de présentation

Discrete Mathematics CS 2610

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Computing Fundamentals 1 Lecture 3

Computing Fundamentals 1 Lecture 3. Lecturer: Patrick Browne http://www.comp.dit.ie/pbrowne/ Room K308 Based on Chapter 3 Propositional Calculus. A Logical approach to Discrete Math By David Gries and Fred B. Schneider. Need for formalism 1. It is difficult to reason in natural language:

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Notes 7: Knowledge Representation, The Propositional Calculus

Notes 7: Knowledge Representation, The Propositional Calculus. ICS 271 Fall 2008. Outline. Representing knowledge using logic Agent that reason logically A knowledge based agent Representing and reasoning with logic Propositional logic Syntax Semantic validity and models

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CMSC 471 Fall 2011 Class #11 Thursday, October 6 Propositional and First-Order Logic

Professor Marie desJardins, mariedj@cs.umbc.edu. CMSC 471 Fall 2011 Class #11 Thursday, October 6 Propositional and First-Order Logic. Chapter 7.4-7.8. Propositional Logic. Some material adopted from notes by Andreas Geyer-Schulz and Chuck Dyer. Propositional Logic.

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CMSC 671 Fall 2005

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CMSC 671 Fall 2005

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CMSC 671 Fall 2005

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Brief Introduction to Logic

Brief Introduction to Logic. Outline. Historical View Propositional Logic : Syntax Propositional Logic : Semantics Satisfiability Natural Deduction : Proofs. Historical view. Philosophical Logic 500 BC to 19th Century Symbolic Logic Mid to late 19th Century Mathematical Logic

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Inference and Explanation

Inference and Explanation. Dr. Adil Yousif. What Is Logic?. Logic is concerned with reasoning and the validity of arguments. we are not concerned with the truth of statements, but rather with their validity .

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Knowledge Representation

Knowledge Representation. Outline: Output - Knowledge representation. Decision tables Decision trees Decision rules Rules involving relations Instance-based representation Prototypes, Clusters. witten&eibe. Output: representing structural patterns.

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Inference in first-order logic

Inference in first-order logic. Chapter 9. Outline. Reducing first-order inference to propositional inference Unification Generalized Modus Ponens Forward chaining Backward chaining Resolution. Universal instantiation (UI).

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1 st -order Predicate Logic (FOL)

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Decision Procedures An Algorithmic Point of View

Decision Procedures An Algorithmic Point of View. BDDs. Part I. Reminders - What is Logic Proofs by deduction Proofs by enumeration Decidability, Soundness and Completeness some notes on Propositional Logic Deciding Propositional Logic SAT tools BDDs. ?. ?. ?. ?. ?. ?.

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Knowledge Representation I

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Machine Learning: Lecture 9

Machine Learning: Lecture 9. Rule Learning / Inductive Logic Programming. Learning Rules. One of the most expressive and human readable representations for learned hypotheses is sets of production rules ( if-then rules).

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AI Application Areas

AI Application Areas. Neural Networks and Genetic Algorithms These model the structure of neurons in the brain Humans are good at interpreting noisy input. Neural networks can also handle noisy data because they use a large number of fine-grained units

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Knowledge Based Systems: Logic and Deduction

Knowledge Based Systems: Logic and Deduction. Department of Computer Science & Engineering Indian Institute of Technology Kharagpur. Knowledge and Reasoning. Representation, Reasoning and Logic Propositional Logic First-Order Logic Inference in first-order logic Generalized Modus Ponens

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CA 208 Continuous Assessment 2006/7

CA 208 Continuous Assessment 2006/7. Name: _______________________________ Student Number: _______________________ Signature: Date: . CA 208 Continuous Assessment 2006/7.

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