Tentamen. Artificial Intelligence December , kl 08:00. The exam consists of exercises worth 30 points. To pass the exam you need 15 points.

Transcription

1 ÖREBRO UNIVERSITET Institutionen för teknik Mathias Broxvall Tentamen Artificial Intelligence December , kl 08:00 Points: Auxiliary items: Directions: Jour: The exam consists of exercises worth 30 points. To pass the exam you need 15 points. Dictionary, calculator. You can answer the questions in English or Swedish. Use notions and methods that have been discussed in the course. Make acceptable assumptions when an exercise has been specified incomplete. Begin each exercise on a new page. Write only at one side of the paper. Write clearly. Mathias Broxvall, tel 1438 The result of the exam will be available January 7th 2004 and it will be possible to check the corrected exams January 7th 2004 from 13 till 15 at my office (T2232) Good luck! 1

2 Exercise 1. [4 p] Explain the following concepts and how they relate to each other. a) Weak AI. b) Strong AI. c) Connectionistic AI. d) Symbol based AI. Exercise 2. [3 p] Assume that we are programming an agent trapped in a maze consisting of a number of rooms and corridors between the rooms and we want to write a search routine for finding a specific room (the exit). That is, we want to find a sequence of rooms that are all connected by corridors such that the last room is the exit. To our help we have a function that given a specific room returns a (alphabetically) sorted list of neighbouring rooms. a) Demonstrate how the system would work and in which order the rooms would be visited if we solved this problem using simple depth first search with loop detection. b) Assume that we run the depth first search without loop detection, what would happend now? c) Assume on the other hand that we are using breadth first search, in which order would the rooms now be investigated. 2

3 Exercise 3. [3 p] a) What is forward chaining how is it used in expert systems. b) What is backward chaining and how is it used in expert systems. c) You have been asked if it would be a good idea to build an expert system to help people decide whether a mushroom is edible or poisonous. Do you think this is a good idea? If it is, give three example rules for the system and if not, motivate why. Exercise 4. [4 p] a) What is a reactive agent. Give a simple example of a reactive agent and discuss the disadvantages of having purely reactive agents. b) What is a utility based agent and what is a utility function. c) What is planning and how is it used in AI agents. d) What is the blocks world domain and how is it defined? Exercise 5. [4 p] Translate the sentences below into first order predicate logic, for each predicate you introduce also give a description of the meaning of the predicate. a) Santa Claus and Rudolf are literary figures and Rudolf have seen Santa Claus. b) Some literary figures are real and some literary figures are not real. c) All non literary figures are real. d) If some person have seen someone else then either both must be real or both non real. 3

4 Exercise 6. [4 p] a) Explain what resolution is, how it works and how it is used in logics. b) Assume that we are using propositional logic for describing information and doing deduction. Given the clauses below, prove using resolution that the proposition P must hold. (A B P ) ( B C) (B C) ( A P ) (A C P ) Exercise 7. [4 p] a) Show, by writing the parse tree, that the sentence The young man saw a girl can be recognized by the grammar below. b) What does it mean for a sentence to be syntactically ambigous and give an example (using the grammar below) of a syntacically ambigous sentence. You may add extra nouns, verbs and adjectives to the grammar if needed. S NP VP VP V VP V NP VP V NP PP NP N NP DET NP NP ADJ NP NP NP PP PP P NP DET the a ADJ young V saw N man girl glasses hat P with on in 4

5 Exercise 8. [4 p] Write a recursive function bin-apply that takes a binary function f and a list l and applies f to all the elements in the list as follows: (bin-apply f (1 2)) is the same as (f 1 2) (bin-apply f ( )) is the same as (f 1 (f 2 (f 3 4))). Thus, some examples of what we would get if we use your new function. (bin-apply # + ( )) => 10 (bin-apply # / (4 1 2)) => 8 5