Overview I. Whither modal semantics? II. A. Modal syntax.

Slides:



Advertisements
Similar presentations
PROOF BY CONTRADICTION
Advertisements

Techniques for Proving the Completeness of a Proof System Hongseok Yang Seoul National University Cristiano Calcagno Imperial College.
Possible World Semantics for Modal Logic
Rigorous Software Development CSCI-GA Instructor: Thomas Wies Spring 2012 Lecture 11.
CS128 – Discrete Mathematics for Computer Science
1 CA 208 Logic Ex1 In your own words, define the following 1. Logic: 2. Valid reasoning/inference (2 equivalent definitions): 3. Propositions/statements:
CPSC 322, Lecture 21Slide 1 Bottom Up: Soundness and Completeness Computer Science cpsc322, Lecture 21 (Textbook Chpt 5.2) February, 27, 2009.
Artificial Intelligence Modal Logic
CPSC 322, Lecture 20Slide 1 Propositional Definite Clause Logic: Syntax, Semantics and Bottom-up Proofs Computer Science cpsc322, Lecture 20 (Textbook.
Formalizing Alpha: Soundness and Completeness Bram van Heuveln Dept. of Cognitive Science RPI.
1 CA 208 Logic Ex3 Define logical entailment  in terms of material implication  Define logical consequence |= (here the semantic consequence relation.
Essential Deduction Techniques of Constructing Formal Expressions and Evaluating Attempts to Create Valid Arguments.
1 Chapter 7 Propositional and Predicate Logic. 2 Chapter 7 Contents (1) l What is Logic? l Logical Operators l Translating between English and Logic l.
Logic. what is an argument? People argue all the time ― that is, they have arguments.  It is not often, however, that in the course of having an argument.
CPSC 322, Lecture 21Slide 1 Bottom Up: Soundness and Completeness Computer Science cpsc322, Lecture 21 (Textbook Chpt 5.2) March, 5, 2010.
Essential Deduction Techniques of Constructing Formal Expressions Evaluating Attempts to Create Valid Arguments.
Proof by Deduction. Deductions and Formal Proofs A deduction is a sequence of logic statements, each of which is known or assumed to be true A formal.
Mathematical Induction
Introduction to Proofs
Intro. to Logic CS402 Fall Propositional Calculus - Semantics (2/3) Propositional Calculus - Semantics (2/3) Moonzoo Kim CS Division of EECS Dept.
(CSC 102) Lecture 3 Discrete Structures. Previous Lecture Summary Logical Equivalences. De Morgan’s laws. Tautologies and Contradictions. Laws of Logic.
Reasoning Top-down biases symbolic distance effects semantic congruity effects Formal logic syllogisms conditional reasoning.
The Inverse Error Jeffrey Martinez Math 170 Dr. Lipika Deka 10/15/13.
Slide 1 Propositional Definite Clause Logic: Syntax, Semantics and Bottom-up Proofs Jim Little UBC CS 322 – CSP October 20, 2014.
LDK R Logics for Data and Knowledge Representation PL of Classes.
Lecture Propositional Equivalences. Compound Propositions Compound propositions are made by combining existing propositions using logical operators.
4 Categorical Propositions
ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.
Validity and Conditionals There is a relationship between validity of an argument and a corresponding conditional.
Logics for Data and Knowledge Representation ClassL (part 1): syntax and semantics.
1 CA 208 Logic PQ PQPQPQPQPQPQPQPQ
LECTURE LECTURE Propositional Logic Syntax 1 Source: MIT OpenCourseWare.
Logical Agents Chapter 7. Outline Knowledge-based agents Logic in general Propositional (Boolean) logic Equivalence, validity, satisfiability.
Proof of Invalidity Kareem Khalifa Department of Philosophy Middlebury College.
CS6133 Software Specification and Verification
2.1 Sets 2.2 Set Operations –Set Operations –Venn Diagrams –Set Identities –Union and Intersection of Indexed Collections 2.3 Functions 2.4 Sequences and.
Propositional SAT The search for a model of a given proposition.
1 Section 8.3 Higher-Order Logic A logic is higher-order if it allows predicate names or function names to be quantified or to be arguments of a predicate.
Conditionality What does TFF mean?. The paradox of material implication p ⊨ q ⊃ p is valid (by the definition of the truth table of ⊃ ) but trivially.
Propositional Logic Rather than jumping right into FOL, we begin with propositional logic A logic involves: §Language (with a syntax) §Semantics §Proof.
ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus.
Artificial Intelligence Knowledge Representation.
Chapter Eight Predicate Logic Semantics. 1. Interpretations in Predicate Logic An argument is valid in predicate logic iff there is no valuation on which.
Logics for Data and Knowledge Representation ClassL (part 1): syntax and semantics.
NEW FOUNDATIONS FOR IMPERATIVE LOGIC III: A General Definition of Argument Validity Peter B. M. Vranas University of Wisconsin-Madison.
Propositional Logic (a.k.a. Sentential Logic)
Chapter 7. Propositional and Predicate Logic
2. The Logic of Compound Statements Summary
COMP 1380 Discrete Structures I Thompson Rivers University
Logics for Data and Knowledge Representation
Jeffrey Martinez Math 170 Dr. Lipika Deka 10/15/13
Project 2 due date moved to next Wed
Semantics In propositional logic, we associate atoms with propositions about the world. We specify the semantics of our logic, giving it a “meaning”. Such.
Lecture 2 Propositional Logic
Chapter 8 Logic Topics
Module #10: Proof Strategies
Logics for Data and Knowledge Representation
Propositional Logic: exercises
Logical Inferences: A set of premises accompanied by a suggested conclusion regardless of whether or not the conclusion is a logical consequence of the.
Back to “Serious” Topics…
Discrete Mathematics and Its Applications Kenneth H
Logics for Data and Knowledge Representation
Module #10: Proof Strategies
Chapter 7. Propositional and Predicate Logic
Bottom Up: Soundness and Completeness
Bottom Up: Soundness and Completeness
6.4 Truth Tables for Arguments
Bottom Up: Soundness and Completeness
Logics for Data and Knowledge Representation
Presentation transcript:

Overview

I. Whither modal semantics?

II. A. Modal syntax

II.D-E. World Diagrams Interpretation: W = {w 1, w 2, w 3 } R = {,, } v w1 (~p) = v w1 (~q) =1 v w2 (p) = v w2 (q) =1 v w3 (p) = v w3 (~q) =1

World Diagrams So, it’s possible thatq in w 1. Why? v w1 (  q) = 1 since, for some world w’  W w 1 Rw’, v w’ (q) = 1; 0 otherwise. (see w 2 ) Similarly, v w1 (  q) = 0, since for some world w’  W w 1 Rw’, v w’ (q) = 0 (see w 3 )

II. F. Validity An inference is valid if it is truth- preserving at all worlds of all interpretations, i.e.: Φ ╞ Ψ iff for all interpretations and all w  W: if v w (Φ) = 1 then v w (Ψ) = 1

Modal Tableaux: First Step First, let’s imagine that we have possible world semantics but no  and . Then, we’d still have to make the following modifications to the tableaux methods for propositional logic: We’d need to index every proposition with the world on which it is true. We’d start at world 0, asserting the premises and denying the antecedent.

Easy Example: P→Q, P ├ Q 1.P →Q, 0A 2.P, 0A 3.~Q, 0Neg Concl /\ 4. ~P, 0 Q, 01, → 5.X 2,4 X 3,4