Artificial Intelligence Midterm Examination for CSCI 4150, Exams of Computer Science

Download Artificial Intelligence Midterm Examination for CSCI 4150 and more Exams Computer Science in PDF only on Docsity! CSCI 4150: Intro. to Artificial Intelligence Midterm Examination Tuesday October 17, 2000 Name: 1 Assorted search questions The following questions explore differences in the number of nodes evaluated for different search imple- mentations. 1. ( points) Two students each write a correct implementation of breadth first search. They then each write correct implementations of the goal? and get-children functions to solve a problem. How- ever, after running their programs on the same start state, they find that their programs have evalu- ated different numbers of nodes. How can they both have correct implementations yet evaluate different numbers of nodes? Be specific in your answers. 2. ( points) Two students each write a correct implementation of the A* search using the OPEN/CLOSED list formulation. They then run the A* search on the same problem using the same heuristic. Is it possible for them to evaluate different numbers of nodes? Explain why or why not. 3. ( points) Assume we have a search tree with a uniform branching factor . What is the minimum and maximum number of nodes that breadth first search will evaluate to find a solution at depth
? What is the minimum and maximum number of nodes that depth first search will evaluate? Express your answers in terms of the depth
of the solution and the maximum depth  of the tree. 2 Constraint Satisfaction and Iterative Improvement search ( points) The map coloring problem is a good example of a constraint satisfaction problem. The goal is to assign one of four colors to each region of the map so that no two adjacent regions have the same color. The initial assignment of the colors to regions is given below. The four colors (abbreviated on the map below) are Red, Green, Blue, and Yellow. The color of each region is assigned to the variable  . For problem, you are to do two iterations of heuristic repair using the “min-conflicts” heuristic. You can choose variables randomly, and you should also break any ties randomly. Show the color assignments after each iteration and explain your work. 1 4 Game search 1. ( points) (a) Explain the horizon problem for game tree search. (b) What is the space and time complexity of minimax search? (c) What is the space and time complexity of minimax search with alpha-beta pruning? 2. ( points) Suppose we are using minimax search (without alpha-beta pruning) with a depth cutoff of 2 to play a game of Connect 4. It is O’s turn to move; the resulting game tree appears below. The value of the evaluation function for each leaf node is shown.  What value does minimax return on this game tree?  Indicate O’s best move on the tree below. X O X O O O X O X X X O X X O O X O X O X X O O X O X O X O X 1 2 3 4 5 6 7








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  Indicate which leaf nodes are evaluated by circling the value of the leaf node.  What is the value of this tree?  Which is the best move from the root node? 9 7 8 2 11 1 10 3 4 6 12 5                                                                                                       













            MAX MIN MAX 5 Logic Here are some sentences in first order logic that encode knowledge about the “kinship domain:” 1. Father(x, y) Parent(x, y) 2. Mother(x, y) Parent(x, y) 3. Wife(a, b) Married(a, b) 4. Husband(a, b) Married(a, b) 5. Married(j,k) Parent(k, m) Parent(j, m) 6. Sister(s, t) Parent(t, v) Aunt(s, v) 7. Brother(s, t) Parent(t, v) Uncle(s, v) Remember the convention for these two argument predicates is as follows: Father(x, y) means “x is the father of y,” Wife(a, b) means “a is the wife of b,” etc. 5 1. Write additional sentences in Horn normal form for this knowledge base to add definitions for the following new predicates. Use only the predicates introduced above and ones that you will write below. Make your sentences as general as possible! (a) Sibling(g, h): g is a sibling of h (b) Cousin(g, h): g is a cousin of h (c) Grandparent(g, h): g is a grandparent of h 2. For this problem, do either Part A or Part B. Use the chart on the following page to show each step of forward/backward chaining. You should only show the successful attempts at matching rules. (a) Using the original knowledge base (1-7), use forward chaining to add the following sentences:  Father(Homer, Lisa) Mother(Marge, Bart) Wife(Marge, Homer) Sister(Patty, Marge) As an example of filling out the chart for this problem, here’s how you’d start forward chaining on the sentence Husband(Bob, Alice): sentence Term added to KB, or matches with premise(s) to match number Premise sought sentence # substitution conclusion produced 8 Husband(Bob, Alice) 4 a/Bob, b/Alice Married(Bob, Alice) (b) Using the original database (1–7) and the following sentences: 9. Father(Homer, Lisa) 10. Mother(Marge, Bart) 11. Wife(Marge, Homer) 12. Sister(Patty, Marge) do backward chaining to show Aunt(Patty, Lisa). As an example of filling out the chart for this problem, here’s how you might start backward chaining on the sentence Parent(Alice, Bob): Premise sought, or matches with Conclusion to match sentence # substitution premise(s) to match Parent(Alice, Bob) 5 j/Alice, m/Bob Married(Alice, k), Parent(k, m) 6