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KRR Unit 1

The document outlines the course structure for 'Knowledge Representation and Reasoning' (Course Code: 22ML601PC), detailing its objectives, outcomes, and evaluation scheme. It covers key concepts of knowledge representation techniques, ontologies, and various processes involved in knowledge engineering. The course aims to equip students with the ability to analyze, design, and implement knowledge-based systems while understanding the theoretical principles of logic-based representation and reasoning.

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989 views26 pages

KRR Unit 1

The document outlines the course structure for 'Knowledge Representation and Reasoning' (Course Code: 22ML601PC), detailing its objectives, outcomes, and evaluation scheme. It covers key concepts of knowledge representation techniques, ontologies, and various processes involved in knowledge engineering. The course aims to equip students with the ability to analyze, design, and implement knowledge-based systems while understanding the theoretical principles of logic-based representation and reasoning.

Uploaded by

pramod.storage1992
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© © All Rights Reserved
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R22 REGULATIONS NMREC-CSE(AIML)

KNOWLEDGE REPRESENTATION AND REASONING

Scheme of
Scheme of Evaluation
Instruction
CourseCode Hours per Maximum
Title of the Course Duration Credits
week Marks
of SEE
P/ in Hours
L T CIE SEE
D
22ML601PC Knowledge Representation and 3 0 0 3 40 60 3
Reasoning
Course Objectives:
 To investigate the key concepts of Knowledge Representation (KR) techniques and different
notations.
 To integrate the KR view as a knowledge engineering approach to model organizational
knowledge.
 To introduce the study of ontologies as a KR paradigm and applications of ontologies.
 To understand various KR techniques and process, knowledge acquisition and sharing of
ontology.

Course Outcomes:
 Analyze and design knowledge-based systems intended for computer implementation.
 Acquire theoretical knowledge about principles for logic-based representation and reasoning.
 Ability to understand knowledge-engineering process
 Ability to implement production systems, frames, inheritance systems and approaches to
handle uncertain or incomplete knowledge.

UNIT - I
The Key Concepts: Knowledge, Representation, Reasoning, Why knowledge representation and
reasoning, Role of logic
Logic: Historical background, Representing knowledge in logic, Varieties of logic, Name, Type,
Measures, Unity Amidst diversity

UNIT - II
Ontology: Ontological categories, Philosophical background, Top-level categories, Describing physical
entities, Defining abstractions, Sets, Collections, Types and Categories, Space and Time

UNIT - III
Knowledge Representations: Knowledge Engineering, Representing structure in frames, Rules and
data, Object-oriented systems, Natural language Semantics, Levels of representation

UNIT - IV
Processes: Times, Events and Situations, Classification of processes, Procedures, Processes and
Histories, Concurrent processes, Computation, Constraint satisfaction, Change Contexts: Syntax of
contexts, Semantics of contexts, First-order reasoning in contexts, Modal reasoning in contexts,
Encapsulating objects in contexts.

UNIT - V
Knowledge Soup: Vagueness, Uncertainty, Randomness and Ignorance, Limitations of logic, Fuzzy
logic, Nonmonotonic Logic, Theories, Models and the world, Semiotics Knowledge Acquisition and
Sharing: Sharing Ontologies, Conceptual schema, Accommodating multiple paradigms, Relating
different knowledge representations, Language patterns, Tools for knowledge acquisition

TEXT BOOKS:

Page 2
R22 REGULATIONS NMREC-CSE(AIML)
1. Knowledge Representation logical, Philosophical, and Computational Foundations by John F.
Sowa, Thomson Learning.
2. Knowledge Representation and Reasoning by Ronald J. Brachman, Hector J. Levesque,
Elsevier.

Page 2
UNIT - 1

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