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Artificial Intelligence In The 21st Century 2nd Edition Stephen Lucci, Danny Kopec - Solutions
3. How would you get three blocks on Table X to be stacked on Table Y in the order A, B, C with block A on top? What operator(s) do you need in addition to those in Problem 2?
2. In the World of STRIPS, use the standard operators and actions to place three blocks—A, B, C—on top of each other on a table starting in the state, A is on C and B is on the table.
1. Recall the Donkey Puzzle presented in Chapter 3. Explain how you would define subgoals to solve this problem. How would a program recognize when the subgoals have been accomplished? Are there any preconditions to the subgoals?
18. Name several areas where practical planners have been built.
17. What does O-Plan offer that the earlier planners didn’t?
16. What was the main feature of NONLIN?
15. What is Sussman’s Anomaly?
14. What is “One-Then-Best Backtracking”?
13. How did NOAH improve on what STRIPS started?
12. Name and describe five planning techniques.
11. Distinguish between partially and totally ordered planning.
10. What is the Frame Problem? What is the Qualification Problem? What is the ‘Ramification Problem’?
9. How would you distinguish planning from other kinds of play in games?
8. Explain how means-ends analysis works.
7. What is least-commitment search?
6. Name five different kinds of search methods in planning.
5. What system was developed to generalize on this system?
4. What is the system that many future planning systems were based on? Where was it developed? What could it do?
3. What was the first problem-solving system that performed planning? What was its purpose?
2. What are the essential components of a plan in the computer sense?
1. Why would one want to get a computer to be able to plan?
15. Explain the trends in NLP during the past 10–20 years. What are the challenges of Information Extraction?
14. Explain the difference between traditional Markov Chains and the Hidden Markov Model.
13. Consider the following grammar and the sentential forms it could produce. Draw a parse tree to demonstrate how the output strings below may be generated.S → aAb | bBA A → ab | aAB B → aB | ba. aaAbbb. bBabc. aaAbBb
12. Consider the following CFG that generates sequences of letters:S -> a X c X -> b X c X -> b X d X -> b X e X -> c X e X -> f X X -> ga. If you had to write a parser for this grammar, would it be more efficient to use a top-down or bottom-up approach? Explain why.b. Trace the approach of your
11. Identify the different senses of the verb “roll” in the following sentences, and give an informal definition of each meaning. Try to identify how each different sense allows different conclusions to be made from each sentence (you may use a dictionary).We rolled the log onto the river.The
10. Bar-Hillel was astonished that no one had ever pointed out that in language understanding there is a world-modeling process going on in the mind of the listener. In what ways is this observation related to the basic hypothesis of conceptual dependency theory?
9. Write as many interpretations as you can of the sentence:“Tom saw his dog in the park with the new glasses.”
8. Experience indicates that the average programmer produces N lines of documented, debugged code per day, on the average, for which N is some number less than 10. High-level code is typically n1 times as efficient as assembly code (i.e., a given job requires 1/n1 times as many lines of code as
7. Winograd observes that the problem of determining the correct time context can be seen with the following sentences:a. Many rich people made their fortunes during the depression.b. Many rich people lost their fortunes during the depression.c. Many rich people worked in restaurants during the
6. Obtain a copy of the early ELIZA program and run several pages of conversation with her.You should include reference to “computers,” family (mother, father, etc.), and perhaps use harsh language.What patterns do you observe?
5. Describe how natural language processing has turned from the early ideals of AI researchers—clearly trying to distinguish syntax from semantics—to more recent approaches?
4. What was the concept behind the development of extended grammars?
3. Have a field day in parsing two of Yogi Berra’s famous phrases:“It’s getting late early”; and “That place is getting too crowded so nobody goes there anymore.”What are the syntactic and semantic issues here?
2. Write two context-free grammars to generate this sentence: “Time flies like an arrow.”
1. Explain the kind of difficulties that machine translation encountered.
24. What does Charniak see as the future of NLP and AI?
23. Describe the Penn Treebank Project.
22. Describe some of the main elements of Information Extraction.
21. What is the noisy-channel model?
20. What was one of the main efforts that led to the success of this approach?
19. Describe when and how statistical systems became prevalent in NLP systems.
18. What were the features of Schanks’ MARGIE, SAM, and PAM systems?
17. What is an HMM and how is it different from a Markov chain?
16. What is the CYK Algorithm and how does it work?
15. Describe the features of a finite state transition network.
14. What is a semantic grammar, who developed it, and for what system?
13. What is a case grammar?
12. What is a systemic grammar?
11. What is a transformational grammar?
10. Describe two features of Prolog that make it suitable for NLP.
9. Give an example of a regular grammar.
8. Describe the Chomsky Hierarchy of Grammars.
7. Describe five classes of understanding in terms of language.
6. Describe briefly the six periods of Natural Language Processing.
5. Research what Henri Kucera did to build the Brown Corpus.
4. Have they been accomplished after some 50 years?
3. What were the goals of machine translation?
2. Explain why language can be diabolical.
1. Describe some of the typical ambiguities of language.
14. In the Euclidean TSP, vertices are randomly placed in some square box (see Figure 12.37). No cost matrix is provided, as the distance between two points, P1 and P2, can be calculated by:d(P1, P2) = sqrt((x2 – x1)2 + (y2 – y1)2). Write a program to solve an instance of the Euclidean TSP when
13. Write a program that uses S-ACO to solve the shortest path problem described in Chapter 2. Test your program on the map of northern China depicted in Figure 2.14(a). Experiment with various pheromone deposit levels. Also, compare results obtained when pheromone evaporation is not (is) employed.
12. Write a program that uses TS to find a minimum k-tree in a graph. Test your program on the graph shown in Figure 12.36, with k = 4.Your program begins with a greedy-based solution that selects the minimal cost edge first and 3 additional edges that are adjacent to this edge (depicted by bold
11. The minimum k-tree problem is to find a tree T in a labeled graph such that T has k edges and the total cost is minimal. For the graph shown in Figure 12.35, minimum 3-tree has a cost = 9.
10. Write a program that uses GP to solve the Tower of Hanoi Problem (consult Chapter 6) for n = 3 discs.
9. Write a program that uses GP to determine the chromatic number of a graph. Test your program on the graphs depicted in Figures 2.39 and 2.40.
8. Write a program that uses GP to construct a full adder.
7. Write a program that uses a GA to develop a strategy for the iterated Prisoner’s Dilemma.Use Koza’s ramped-half-and-half method to form the initial population for each of problems 8 and 9. Experiment with various values of m and d.
6. Write a program for a GA-based tic-tac-toe player.
5. Write a program to have a GA solve the 15-puzzle. The input to your program is a random arrangement of the tiles. The output is the tiles in order or a message that a solution is not possible (recall that half of the arrangements will not be reachable).
4. Write a program to have a GA determine the chromatic number of a graph (see Exercise 4).Test your program on the graphs depicted in Figures 2.39 and 2.40.
3. Write a program to have a GA solve the Missionaries and Cannibals problem (see Exercise 3).
2. Write a program to have a GA solve the 4-Queens problem (see Exercise 2).
1. Write a program that uses Monte Carlo simulation to approximate the value of π. (See Exercise 1 above). Use pairs of random numbers over [0, 1) instead of darts.
9. Until Darwin’s theory of evolution, people believed that living systems were designed by God (or a God-like figure). William Paley was a theologian who proposed in the 1802 book Natural Theology 48 his watchmaker argument: A watch is a complex artifact. If you were to find a watch on the side
8. Design a GP to determine the chromatic number of a graph (see Exercise 12.3). You will need to use functions thata. Assign a color to a node.b. Change the color of a node when necessary.c. Keep count of the number of colors used.
7. How would you design a GA-based strategy for the iterated Prisoner’s Dilemma (Chapter 4)?
6. How would you formulate a GA that is capable of playing tic-tac-toe?
5. Design a GA solution for the 15-puzzle.
4. Design a GA solution for determining the chromatic number of a graph (Chapter 2). How does your fitness function avoid infeasible solutions? How does it reward solutions using fewer colors?
3. Design a GA solution for the Missionaries and Cannibals problem (Chapter 2). How does your fitness function measure closeness to the goal? How does it prevent unsafe states from occurring?
2. Design a GA solution for the 4-Queens problem (Chapter 2). Be sure to specify your representation and your fitness function.
1. Drawn on the dartboard is ¼ of a circle as shown. You throw 100 darts at the board. Assume that all darts land randomly somewhere on the board.How can you use this experiment to approximate the value of π?
18. Cite several future applications for swarm robotics at both the macroscopic and microscopic level.
17. What possible applications do you envision for the cemetery formation example?
16. Observe that in Figure 12.32, some ants do not follow the shortest path from the nest to a food source. What useful purposes do these supposedly misguided foragers play?
15. Explain the role that pheromone evaporation plays in the shortest path example explained in Section 5.
14. What is stigmergy? Why is this a useful means of communication?
13. List three aspiration criteria in tabu search and explain why they are helpful.
12.a. In tabu search, do tabu lists encourage exploitation or exploration?b. Same question for aspiration lists?
11. What problems do you foresee in selection of tree heights in GP? How does Koza’s rampedhalf-and-half method address this problem?
10. What is the major distinction between GA and GP?
9. A genetic operator not discussed for GA is inversion. Choose two sites randomly on a chromosome: 10^0100^11, and then reverse all characters between these two points as:10001012.a. First, what possible problem do you believe inversion is trying to correct?b. Second, what is wrong with the way we
8. Suppose that you are using a GA to solve an instance of the TSP. What precautions must be taken when performing crossover?
7. One selection algorithm not discussed is that of miser selection, in which the worst member of a population is selected to participate in reproduction. What advantages do you foresee for this approach?a. What advantages do you foresee in increasing the population size in a GA?b. What
6. Which operator do you believe is more useful to a GA—crossover or mutation? Defend your assertion.
5. Explain the genetic operators: selection, crossover, and mutation used in GA.
4. How does the temperature parameter T help SA to balance exploitation and exploration?
3. What is the disadvantage of favoring exploitation over exploration in a search (hint: think of hill climbing)?
2. Define exploitation and exploration in search algorithms.
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