AI Course Fundamental | Knowledge Representation and Reasoning by Diljeet Singh | Learn Smarter
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Knowledge
Knowledge Representation and Reasoning

Knowledge Representation (KR) is crucial in AI, allowing for the encoding and manipulation of information. The chapter discusses logic-based representations, focusing on Propositional and First-Order Logic, as well as Ontologies and Semantic Networks. These methods help create intelligent systems capable of reasoning and making informed decisions in complex domains.

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Sections

  • 4

    Knowledge Representation And Reasoning

    Knowledge Representation (KR) is essential in AI for encoding and manipulating information to enable reasoning and decision-making.

    Learning Practice

  • 4.1

    Introduction To Knowledge Representation

    Knowledge Representation (KR) enables machines to represent and manipulate knowledge, forming the basis of reasoning in Artificial Intelligence.

    Learning Practice

  • 4.2

    Logic-Based Representations

    Logic provides a formal framework for knowledge representation, enabling machines to express, reason, and infer knowledge efficiently.

    Learning Practice

  • 4.2.1

    Why Use Logic?

    Logic provides a formal foundation for knowledge representation, facilitating precise expression and deduction.

    Learning Practice

  • 4.2.2

    Types Of Logic In Ai

    This section outlines the various types of logic used in AI for knowledge representation.

    Learning Practice

  • 4.3

    Propositional And First-Order Logic

    This section explores propositional and first-order logic, key concepts in knowledge representation and reasoning in AI.

    Learning Practice

  • 4.3.1

    Propositional Logic

    Propositional logic represents statements that can be either true or false, focusing on syntax and semantics of propositions.

    Learning Practice

  • 4.3.2

    First-Order Logic (Fol)

    First-Order Logic extends propositional logic by incorporating variables, quantifiers, and predicates, allowing for the representation of complex relationships.

    Learning Practice

  • 4.4

    Ontologies And Semantic Networks

    Learning

  • 4.4.1

    Ontologies

    An ontology is a formal framework for organizing knowledge, defining concepts, relationships, and constraints within a specific domain.

    Learning Practice

  • 4.4.2

    Semantic Networks

    Semantic networks are graph-based representations of knowledge that use nodes for concepts and edges for relationships.

    Learning Practice

References

Chapter 4_ Knowledge Representation and Reasoning.pdf

Class Notes

Memorization

What we have learnt

  • Knowledge Representation is...
  • Logic provides a formal fra...
  • Ontologies and Semantic Net...

Final Test

Revision Tests