Lecture 6 - Knowledge Representation - MITI 5113 ARTIFICIAL...

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MITI 5113 ARTIFICIAL INTELLIGENCE Lecture 6 Lecture 6 Knowledge Representation Knowledge Representation 04/16/1 7 1
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Introduction to KR An area in artificial intelligence that is concerned with how to use a symbol system to represent “a domain of discourse” They display the implicit knowledge about a subject in a form that programmers can encode in algorithms and data structures. This part of the course is about knowledge-base analysis and design: To analyze knowledge about the real world and map it to a computable form, which we address two fundamental issues how to represent knowledge how to implement the process of reasoning 04/16/17 2
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What is Knowledge? What is Knowledge? Data Data – primitive verifiable facts, of any – primitive verifiable facts, of any representation. Data reflects the current representation. Data reflects the current world. world. Knowledge Knowledge – relation among sets of data – relation among sets of data (information), that is very often used for (information), that is very often used for further information deduction. further information deduction. Knowledge contain information about Knowledge contain information about behaviour of abstract models of the world. behaviour of abstract models of the world. 04/16/17 3
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Motivation Search Vision Planning Machine Learning Knowledge Representation Logic Expert Systems Robotics NLP 04/16/17 4
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Representation of Knowledge Representation of Knowledge There is no single most adequate no single most adequate knowledge representation formalism/scheme for everything. A KR language is defined by two aspects: Syntax : describes how to make sentences OR describes the possible configurations that can constitute sentences. Semantics : determine the facts (meaning) in the world to which the sentences refer OR the “things” in the sentence. 04/16/17 5
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Classification Knowledge Representation Unstructured Structured Primitive Oriented Predicate calculus Semantic Nets Frames Conceptual Dependencies Scripts 04/16/17 6
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Predicate Calculus By Gottlob Frege (German Mathematician: 1848- 1925) Key points Simplest type of representation Fully logic based Deduction, Abduction and Induction Application: In rule-based systems 04/16/17 7
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Knowledge Representation Knowledge Representation Predicate Calculus Predicate Calculus Propositional Logic (Propositional Calculus): Propositional Logic has limitations, - it is not expressive enough. First-order Logic (First-order Predicate Calculus): First-Order Logic is an improvement and is useful. 04/16/17 8
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Propositions Propositions Statements that can be either true or false The sky is blue The moon is made of cheese Artificial intelligence is my favourite subject Each statement takes one of the truth- values T or F (or, 1 and 0) Each statement is represented by a propositional variable such as p , q , r , 04/16/17 9
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Logical operators Logical operators We can use logical operators (or connectives ) to build more complex statements from our simple propositions The moon is not made of cheese I am bored and I am tired You are a man or you are a mouse If it is snowing then it is cold 04/16/17 10
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  • Winter '14
  • STUDENT
  • Logic, Logical connective, Propositional calculus, First-order logic

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