'General unifier' presentation slideshows

Knowledge Repn. & Reasoning Lec. #6: First-Order Inference

Knowledge Repn. & Reasoning Lec. #6: First-Order Inference. UIUC CS 498: Section EA Professor: Eyal Amir Fall Semester 2004. Today. Until now: First-order logic basics Clausal form for FOL Resolution refutation for FOL Application du jour: Temporal Reasoning

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CS498-EA Reasoning in AI Lecture #7

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Inductive Logic Programming: The Problem Specification

Inductive Logic Programming: The Problem Specification. Given : Examples: first-order atoms or definite clauses, each labeled positive or negative. Background knowledge: in the form of a definite clause theory. Language bias: constraints on the form of interesting new clauses.

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Inductive Logic Programming: The Problem Specification

Inductive Logic Programming: The Problem Specification. Given : Examples: first-order atoms or definite clauses, each labeled positive or negative. Background knowledge: in the form of a definite clause theory. Language bias: constraints on the form of interesting new clauses.

477 views • 33 slides

Resolution Preliminaries

Computational Logic Lecture 9. Resolution Preliminaries. Michael Genesereth Autumn 2011. Difficulty with Universal Instantiation. Resolution Principle. The Resolution Principle is a rule of inference.

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Resolution Preliminaries

Computational Logic Lecture 9. Resolution Preliminaries. Michael Genesereth Autumn 2006. Resolution Principle. The Resolution Principle is a rule of inference.

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Resolution

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Chapter 2 & 3 (Part 2): A Representation & Reasoning System & Using Definite Knowledge

Chapter 2 & 3 (Part 2): A Representation & Reasoning System & Using Definite Knowledge. Proofs (2.7) (How to compute logical consequences of a KB rather that testing whether a given formula is a KB logical consequence?) Functions Symbols: Language Extension (2.8)

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Chapter 2 & 3 (Part 2): A Representation & Reasoning System & Using Definite Knowledge

Chapter 2 & 3 (Part 2): A Representation & Reasoning System & Using Definite Knowledge. Proofs (2.7) (How to compute logical consequences ?) Functions Symbols: Language Extension (2.8) Representing Abstract Concepts (3.5).

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Chapter 8 Inference and Resolution for Problem Solving

Chapter 8 Inference and Resolution for Problem Solving. Chapter 8 Contents (1). Normal Forms Converting to CNF Clauses The Resolution Rule Resolution Refutation Proof by Refutation Example: Graph Coloring. Chapter 8 Contents (2). Normal Forms in Predicate Calculus Skolemization

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Inference in FOL

Inference in FOL. All rules of inference for propositional logic apply to first-order logic We just need to reduce FOL sentences to PL sentences by instantiating variables and removing quantifiers. Reduction of FOL to PL. Suppose the KB contains the following :

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Predicate Calculus 2

Predicate Calculus 2. Outline: Unification: definitions, algorithm Formal interpretations and satisfiability Horn clauses and PROLOG. Unification. Predicate calculus rules are sometimes so general that we need to create specializations of them in order to perform resolution.

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Predicate Calculus 2

Predicate Calculus 2. Outline: Unification: definitions, algorithm Formal interpretations and satisfiability Horn clauses and PROLOG. Unification. Predicate calculus rules are sometimes so general that we need to create specializations of them in order to perform resolution.

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Chapter 8 Inference and Resolution for Problem Solving

Chapter 8 Inference and Resolution for Problem Solving. Chapter 8 Contents (1). Normal Forms Converting to CNF Clauses The Resolution Rule Resolution Refutation Proof by Refutation Example: Graph Coloring. Chapter 8 Contents (2). Normal Forms in Predicate Calculus Skolemization

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Artificial Intelligence Tutorials

Artificial Intelligence Tutorials. Tutorial # 7. Q1: Give the most general unifier if it exists. P(A,B,B) and P( x,y,z ): {x/A, y/B, z/B} Q( y,G (A,B)) and Q(G( x,x ),y): No unifier (x cannot bind to both A and B). Older(Father(y),y) and older(Father(x),Ali): {y/Ali, x/Ali}

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