2003 Course - K. K. Wagh Education Society
2003 Course - K. K. Wagh Education Society 2003 Course - K. K. Wagh Education Society
Code Optimisation Introduction, Classification of optimisation, Principle sources Of Optimisation, optimisation of basic blocks, Loops in flow graphs, Optimising transformations: compile time evaluation, Common sub-expression elimination, variable propagation, code movement, strength reduction, dead code elimination and loop optimisation, Local optimisation, DAG based local optimisation. Global Optimisation: Control and data flow analysis, Computing Global Data flow information: meet over paths, Data flow equations, Data flow analysis, Iterative data flow analysis: Available expressions, live range identification Text Books 8 Hours 1. A V Aho, R. Sethi, J D Ullman, “Compilers: Principles, Techniques, and Reference Books Tools”, Pearson Education, ISBN 81 – 7758 – 590 – 8 1. K. Cooper, L. Torczon, “Engineering a Compiler”, Morgan Kaufmann Publishers, ISBN 81 – 8147 – 369 – 8 2. K. Louden, “Compiler Construction: Principles and Practice”, Thomson Brookes/Cole (ISE), 2003, ISBN 981 – 243 – 694 – 4 3. J. R. Levine, T. Mason, D. Brown, “Lex & Yacc”, O’Reilly, 2000, ISBN 81–7366 – 062 – X 4.S. Chattopadhyay, “Compiler Design”, Prentice-Hall of India, 2005, ISBN 81– 203–2725-X. 410445 Artificial Intelligence Teaching Scheme Lectures :4 Hrs/Week Examination Scheme Theory :100 Marks Practical. : 2 Hrs/Week Term Work : 25 Marks Oral : 50 Marks Duration : 3 Hrs Objectives • To understand the concepts of Artificial intelligence
• To Learn and Understand the knowledge representation techniques for knowledgebase • To Learn and Understand the fundamentals of Neural Network UNIT I : Introduction Definition, What is A.I ? Foundation of A.I., History, intelligent Agents, Agent Architecture, A.I. Application(E Commerce, & Medicine), A.I. Representation, Properties of internal representation . Futures of A.I ,Production System , Issue in design of search Programs Logic Programming Introduction , Logic, Logic Programming, Forward and Backward resoning , Forward and Backward chaining rules 8 Hrs UNIT II : Heuristic search techniques. Heuristic search, Hill Climbing, Best first search, mean and end analysis, Constraint Satisfaction, A* and AO* Algorithm. Game playing Minmax search procedure, Alpha beta cutoffs, waiting for Quiescence, Secondary search. 7 Hrs. UNIT III : Knowledge Representation Basic of Knowledge representation, Knowledge representation Paradigrams, Propositional Logic, Inference Rules in Propositional Logic, Knowledge representation using Predicate logic : Predicate Calculus, Predicate and arguments, ISA hierarchy, Frame notation , Resolution , Natural Dedication
- Page 1 and 2: Structure of B.E (2003 Course):- De
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- Page 5 and 6: Background, Critical section proble
- Page 7 and 8: Teaching Scheme Lectures: 3 Hours /
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- Page 17 and 18: UNIT IV : Segmentation : Region Ext
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- Page 29 and 30: Principles, RSA, ECC, DSA, key mana
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• To Learn and Understand the knowledge representation techniques for<br />
knowledgebase<br />
• To Learn and Understand the fundamentals of Neural Network<br />
UNIT I :<br />
Introduction<br />
Definition, What is A.I ? Foundation of A.I., History, intelligent Agents, Agent<br />
Architecture, A.I. Application(E Commerce, & Medicine), A.I. Representation,<br />
Properties of internal representation . Futures of A.I ,Production System , Issue in<br />
design of search Programs<br />
Logic Programming<br />
Introduction , Logic, Logic Programming, Forward and Backward resoning , Forward<br />
and Backward chaining rules 8<br />
Hrs<br />
UNIT II :<br />
Heuristic search techniques.<br />
Heuristic search, Hill Climbing, Best first search, mean and end analysis, Constraint<br />
Satisfaction, A* and AO* Algorithm.<br />
Game playing<br />
Minmax search procedure, Alpha beta cutoffs, waiting for Quiescence, Secondary<br />
search. 7 Hrs.<br />
UNIT III :<br />
Knowledge Representation<br />
Basic of Knowledge representation, Knowledge representation Paradigrams,<br />
Propositional Logic, Inference Rules in Propositional Logic, Knowledge representation<br />
using Predicate logic : Predicate Calculus, Predicate and arguments, ISA hierarchy,<br />
Frame notation , Resolution , Natural Dedication
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