VTU CSE 7th Semester Artificial Intelligence Question Paper January 2010: You must have Artificial Intelligence Question Paper along with the latest Computer Science 7th sem Syllabus to enhance your semester exam preparation.
To score better marks in the 7th semester, you should also have depth knowledge in the entire subject. You can boost your preparation by solving previous year question papers. It will give you information about the important chapters and concepts to be covered in all chapters.
You must have Artificial Intelligence Question Paper along with the latest Computer Science 7th sem Syllabus to enhance your semester exam preparation.
Here we are providing you the complete guide on Artificial Intelligence Question Paper January 2010.
VTU CSE 7th Semester Artificial Intelligence Question Paper January 2010
VTU CSE 7th Semester Artificial Intelligence Previous year Papers are considered as the best study materials to score good marks in the semester exam. Practicing these previous year question papers assist the students to get a clear idea about the question paper pattern and types of questions that will be asked in the exam.
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Here you can check the Artificial Intelligence Question Paper January 2010
Note: Answer any FIVE full questions, selecting at least TWO questions from each part.
1 a. With examples, explain different types of task environments.
b. Explain Breadth-First-Search (BFS) strategy.
2 a. Explain A* search strategy. Prove :
i) A* using TREE-SEARCH is optimal if h(n) is admissible.
ii) A* using GRAPH-SEARCII is optimal if h(n) is consistent.
b. Write the algorithm for online search agent that uses depth first exploration.
3 a. Write the syntax of propositional logic. Write BNF grammar for sentences in propositional logic.
b. Write the algorithm for Wumpus – world agent to find pits, wupuses and safe squares.
4 a. Write the syntax of first order logic using BNF.
b. List and explain the steps involved in knowledge engineering projects.
5 a. Write toward chaining algorithm.
b. Explain aspects of prolog that fall outside standard logical inference.
6 a. Explain with examples, how first order logic expresses facts about categories.
b. Explain the ontology of situation calculus.
7 a. Compare how STRIPS and ADL programming languages represent planning problems.
b. What is Bayesian network? Explain how it is used to represent knowledge?
8 a. Write the decision tree learning algorithm.
b. Explain how the applicability of decision trees is broadened.
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