| November 10th, 2020 12:54 PM | |
| prince karak | 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 |
