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Default Sathyabama Institute of Science and Technology B.Tech - BioMedical Engineering SBMA4008 Artificial Intelligence and Expert Systems Syllabus

Sathyabama Institute of Science and Technology B.Tech - BioMedical Engineering SBMA4008 Artificial Intelligence and Expert Systems Syllabus

SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY SCHOOL OF MECHANICAL ENGINEERING

SBMA4008 ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS
L T P Credits Total Marks
3 0 0 3 100

UNIT 1 AI AND INTERNAL REPRESENTATION 9 Hrs.
The AI problem–What is AI technology–Level of the Model – Criteria for Success problems, Problem Spaces & Searches &
Heuristic Search Technology Problem as a State Space Search –Production Systems– production System Characteristics –
Generate & Test– Hill Climbing–Best First Search–Constraint Satisfaction– Means End Analysis.

UNIT 2 KNOWLEDGE REPRESENTATION 9 Hrs.
Issues in Knowledge Representation–Using Predicate Logic – Representing Simple Facts in Logic, Representing Instance &
Isa Relationship – Computable Functions & IPredicates–Representing Knowledge Using Rules: Procedural Vs. Declarative
Knowledge–Forward Vs. Backward Reasoning.

UNIT 3 SLOT AND FILLERSTRUCTURES 9 Hrs.
Weak Slot & Filler – Semantic Nets – Frames Strong & filler Structures – Scripts – CYC-CYCL

UNIT 4 EXPERT SYSTEMS 9 Hrs.
Whatare Expert Systems – Knowledge Representationin Expert Systems–Symbolic Computation–Rule based Systems

UNIT 5 TOOLS FOR BUILDING EXPERT SYSTEMS 9 Hrs.
Using Domain Knowledge–Knowledge Acquisition–Design for Explanation–Black Board Architecture– Truth Maintenance
Systems–Machine Learning–Case based Reasoning
Max. 45 Hrs.

COURSE OUTCOMES
On completion of the course, student will be able to
CO1 - Understands the basics of Artificial intelligence and the various searching techniques
CO2 - Analyses the knowledge representation through forward and backward chaining techniques
CO3 - Applies and articulate the knowledge over the design of sementic nets
CO4 - Explains the various expert systems by applying appropriate rule base
CO5 - Evaluates the architecture and frameworks of Truth Maintenance systems through machine Learning algorithms
CO6 - Creates the design of real time AI and expert systems through various case studies

TEXT / REFERENCE BOOKS
1 Elaine Rich, Kevin Knight, Artifical Intelligence, 2nd Edition, Tata McGraw Hill,1992.
2 Peter Jackson, Introduction to Expert Systems, 3rd Edition, Addison Wesley, 1st Indian Reprint, 2000.

END SEMESTER EXAMINATION QUESTION PAPER PATTERN
Max. Marks: 100 Exam Duration: 3 Hrs.
PART A: 10 Questions of 2marks each – No choice 20 Marks
PART B: 2 Questions from each unit of internal choice ;eachcarrying16marks 80 Marks
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