AI Question Bank

R.V.S. COLLEGE OF ENGINEERING AND TECHNOLOGY COIMBATORE - 402 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING ACADEMIC YEAR -2012-2013 QUESTION BANK  Subject: ARTIFICIAL INTELLIGENCE

Class / Sem : IV CSE / VII

UNIT I Introduction and Problem Solving I

Artificial Intelligence: Definition-Turing Test-Relation with other Disciplines-History Disciplines-History of AIApplicationsAIApplicationsAgent: Intelligent Agent-Rational Agent - Nature of Environments- Structure of Agent.-Problem Solving Agent - Problems: Toy Problems and Real-world Problems-Uninformed Search Strategies: BFS, DFS, DLS, IDS, Bidirectional Search - comparison of uninformed search strategies. Part-A 1. Define AI. 2. What is a rational agent? 3. State the factors factors that make up rationality. rationality. 4. What is a task environment? environment? Specify the task environment environment for any two agents. 5. What are the different different types of environment agent percepts percepts and reacts? 6. What is agent agent program and agent agent architecture? 7. List the different different types of agents. 8. What is a software agent? agent? 9. Give the steps adopted adopted by a problem solving solving agent. 10. What is a fringe? 11. What are the various searching strategies adopted by agent programs? 12. Give the problem types for searching based on partial information. Part-B 1. a. Elaborate the approaches for AI with eg.  b. How is a task environment environment specified? 2. a. Describe the various properties of the task environment.  b. Write PEAS description for at least least four agent types. 3. a. Explain in detail Utility based reflex agent.  b. Explain in detail Learning Learning agent. 4. Explain how solutions are searched by a problem solving agent. 5. Write short short notes notes on the the following following uniform uniform cost search and Iterative deepening deepening depth first search. search. 6. Explain Simplex Simplex reflex reflex and model based agent and compare each of them with respective respective to their   behavior. 7. What are the procedures procedures to to formulate formulate the problem and and goal for any toy problem? problem? 8. List the different uninformed searches and explain with an example where Breadth first search is  better than Depth first search. search. 9. Explain Iterative Depth Limited search with an example(limit =4) and uniform cost search. 10. Explain Bidirectional search and compare all the uninformed uninformed search strategies based on their   performance. 11. How searching searching is used used to provide provide solutions solutions and also also describe some real world world problems? problems?

UNIT II Problem Solving II

Inform Informed ed Search Search Strate Strategie gies-G s-Gree reedy dy best-f best-firs irstt search search-A* -A* search search-He -Heuri uristi sticc functi functions ons-Lo -Local cal search search Algor Algorith ithms ms and Optimi Optimizat zation ion proble problems ms - Onlin Onlinee Search Search AgentAgent-Con Constr strain aintt Satisf Satisfact action ion Proble ProblemsmsBacktracking Search for CSP’s –Local Search f or Constraint Satisfaction Problems-Structure Problems-Structure of Problems -Adversarial Search-Optimal Decision in Games-Alpha-Beta Pruning-Imperfect Real Time DecisionsGames that Include an Element of Chance. Part A

1. What What is the the use use of heuri heuristi sticc functi functions ons?? 2. What is the difference between informed and uninformed searches? 3. How does one characterize the quality of heuristic? 4. What What is use use of of local local sear search ch algor algorith ithms? ms? 5. What is is the advan advantage tage of of memory memory bounded bounded search search techn technique iques? s? 6. How to improve improve the the effectivene effectiveness ss of search-bas search-based ed problem-s problem-solvi olving ng techniqu techniques? es? 7. What What is constr constrain aintt satisfa satisfacti ction on probl problem? em? 8. How does does the operatio operation n of offline offline search search differ differ from from an online online search? search? 9. List some drawbacks drawbacks of hill hill climbing climbing process. process. 10. List some some propertie propertiess of SMA* search. search. 11. State the monotonicity monotonicity property in A* search. Part B 1. Write A* A* algorith algorithm m and show show how A* algor algorithm ithm can can be used used to find find minimal-co minimal-cost st over all path or simply any path as quickly as possible

2. Expl Explai ain n Min-Ma Min-Max x proce procedu dure re.. 3. Describe alpha-beta pruning and its effectiveness. 4. Explain Explain Hill Hill climbin climbing g and Simulat Simulated ed Anneali Annealing ng algorit algorithms. hms. 5. Explai Explain n Geneti Geneticc algorit algorithm hm with with exampl example. e. 6. What is constraint satisfaction problem and explain how information is propagated through constraints? 7. How intelligent back tracking is achieved in a CSP? UNIT III Knowledge Representation

First-Orde First-Orderr Logic-Syn Logic-Syntax tax and Semantics Semantics of First-Orde First-Order-Log r-Logic-Us ic-Using ing First-Orde First-Order-Log r-Logic-Kn ic-Knowle owledge dge Engineer Engineering ing in First-Orde First-Order-Log r-Logic.ic.- Inference Inference in First-Ord First-Order-Log er-Logicic- Inference Inference rules-Uni rules-Unificat fication ion and Lifting-Forward Chaining-Backward Chaining-Resolution. Chaining-Resolution. Part A

1. 2. 3. 4. 5.

How does does a logical logical agent agent perform perform in its its environ environment ment?? What What is mean meantt by logi logical cal equiva equivalen lence? ce? Writ Wr itee the the Modu Moduss Pone Ponens ns rul rule. e. What is is meant meant by a term term and and using using term frame frame an atomi atomicc sentence sentence?? What are the the differen differentt quantifie quantifiers rs in a First First Order Order Logic? Logic?

6. What What is skol skolem emiz izat atio ion? n? 7. Give Give an exampl examplee in conjun conjuncti ctive ve norma normall form. form. 8. Translate the following FOL into English : a. ∀x ∃y ( x ≥y )

b. ∀y ∃x (x ≥ y)

9. Write down down the the logical logical represen representatio tations ns for the the following following sente sentences: nces: a.Some students took French in Spring 2001.  b.No one buys an expensive expensive policy. Part B 1. Explain Explain the the syntax syntax and and semant semantics ics of first order order logic. logic. 2. Explain the difference between forward and backward chaining and under what conditions each would be best to use for a given set of problems. 3. Consid Consider er the the foll followi owing ng sent sentenc ences es   John John likes all kinds of food • Apples are food • Chicken is food • Anything anyone eats and isn’t killed by its food • Bill eats peanuts and is still alive • Sue eats everything Bill eats • (a) Translate these sentences into formulas in predicate logic (b) Prove that John likes peanuts using backward chaining (c) Convert the formulas of part a into clause form (d) Prove that John likes peanut using resolution (e) Use resolution to answer the question, “what food does Sue eat?”

UNIT IV Learning

Learning from Observations- Forms of Learning-Learning Decision –Ensemble Learning - A Logical Formulation of Learning-Knowledge in Learning-Explanation Based Learning-Learning using Relevance Information-Inductive Information-Inductive Logic Programming. Part A 1. List the advantages of Decision Trees. What is the function of Decision Trees? 2. Differenti Differentiate ate betwee between n Passive Passive learne learnerr and Activ Activee learner  learner  3. State the design design issues issues that that affect affect the the learning learning element element 4. Differenti Differentiate ate between between superv supervised ised learnin learning g & unsupervis unsupervised ed learning learning.. 5. What What is memo memoiz izat atio ion? n? 6. Defi Define ne Ockh Ockham am’s ’s razo razor. r. 7. List the variou variouss Componen Components ts of the perform performance ance elemen elementt 8. Draw a decision decision tree tree for the problem problem of decidin deciding g whether whether to move forward forward at a road interse intersection ction,, given that the green lights are on.

Part B

1. 2. 3. 4. 5. 6. 7.

Explain Explain Explanat Explanation ion Based Based Learning Learning process process and the the ways to improve improve the the efficiency. efficiency. Explain Explain learning learning using using relevan relevance ce infor informatio mation. n. Explain a Top-Down inductive learning method method that uses a generalization of decision decision tree methods. Explain Explain inductiv inductivee learning learning with inverse inverse deduction deduction based based on invertin inverting g a resoluti resolution on proof. Explain Explain why computat computational ional learni learning ng theory theory is important important and and the use of PAC algori algorithm. thm. List the the forms of learnin learning g and explain explain how decisi decision on trees trees are used as performan performance ce elements. elements. Explain Explain Decision Decision tree tree algorithm algorithm and assess assess the the performance performance of the algori algorithm. thm.

8. Explain Explain ADABOO ADABOOST ST algori algorithm thm for for ensembl ensemblee learnin learning. g.

UNIT V Applications

Communication –Communication as action -A formal grammar for a fragment of English – Syntactic Analy Analysis sis – Augmen Augmented ted Gramma Grammars rs – Semant Semantic ic Interp Interpret retati ation on – Ambigu Ambiguity ity and Disamb Disambigu iguati ation on –  Discourse Understanding – Grammar Induction.Perception –Image Formation –Early Image Processing Operation Operationss – Extractin Extracting g Three Three Dimension Dimensional al Informatio Information n – Object Object Recogniti Recognition on – Using Using Vision Vision for  Manipulation and Navigation. Part A 1. Why ambiguity ambiguity is consider considered ed to be an important important problem problem in natural language language underst understandin anding? g? 2. What What is the the use use of a DCG DCG?? 3. What What is pragma pragmatic tic inter interpre pretat tation ion?? 4. What is a langu language age discours discoursee and give give the struct structure ure of coheren coherentt discourse discourse?? 5. How to to learn learn a gramma grammarr from from a given given data data?? 6. State Lambert’s cosine law. 7. How to to measure measure optical optical flow from one one time time frame frame to the the next? next? 8. What is is the relat relation ion betwee between n disparit disparity y and depth depth in stereopsi stereopsis? s? 9. What are are the differ different ent kinds kinds of of line labeli labeling ng and give exampl examples? es? 10. How does vision vision provide information for manipulating objects? 11. List the models used used for representing knowledge. Part B

1. Explain Explain the componen componentt steps steps of communicat communication. ion. 2. Explain Explain top top down down and and bottom bottom up up parsing parsing with an example. example. 3. Explain Explain with with an exampl examplee the semanti semantics cs of an English English fragmen fragment. t. 4. Parse a tree for the sentence “Every agent smells a wumpus” showing both syntactic and semantic interpretations. 5. Explain Explain the the use of of verb subca subcatego tegorizat rization ion to augment augment grammars grammars.. 6. Explai Explain n the the form formati ation on of an an image image.. 7. Explain Explain edge detecti detection on and segmentati segmentation on that are used used as early image process processing ing operatio operations. ns. 8. How to recover 3-D information from an image and explain the extraction of texture gradients and shading? 9. What are are the approach approaches es for object object recogn recognition ition?? Explain Explain each of of them. them.