Artificial Intelligence: A Modern Approach
3rd Edition
ISBN: 9780136042594
Author: Stuart Russell, Peter Norvig
Publisher: Prentice Hall
expand_more
expand_more
format_list_bulleted
Concept explainers
Expert Solution & Answer
Chapter 5, Problem 10E
a.
Explanation of Solution
Upper bound
- An upper bound on the number of terminal nodes is N!...
b.
Explanation of Solution
Lower bound
- In this case, no bounds will terminate early.
- There are N! dif...
c.
Explanation of Solution
Plausible evaluation function
- For a state s, X(s) is the number of winning positions...
d.
Explanation of Solution
Checking winning position
- Using the upper bound of N!, it takes 100N N! instructions...
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
Model the following game as an adversarial search poblem. Your modeling should be complete and
detailed specifying state representation, actions, terminal test, state values, cutoff evaluation, etc.
There is a board that has six holes. There is a total of 20 small balls that are distributed in the
holes randomly provided that no hole is empty. The game is played in turns by two players. In each
player's turn, the player can remove any number of balls from ONE HOLE ONLY. The player that
removes the last ball from the board loses the game.
A transaction database is a set of transactions completed in a supermarket database. Each transaction is a set of items. For example, consider the following transaction database. It contains 5 transactions (t1, t2, ..., t5) and 5 items (1,2, 3, 4, 5). For example, the first transaction represents the set of items 1, 3 and 4. It is important to note that an item is not allowed to appear twice in the same transaction and that items are assumed to be sorted by lexicographical order in a transaction.
Transaction id
Items
t1
{1, 3, 4}
t2
{2, 3, 5}
t3
{1, 2, 3, 5}
t4
{2, 5}
t5
{1, 2, 3, 5}
What is the output of the Apriori algorithm run on the previous transaction database with a minimum support of 40 % (2 out of 5 transactions)?
You will be given a square chess board with one queen and a number of obstacles placed on it. Determine how many squares the queen can attack.
A queen is standing on an chessboard. The chess board's rows are numbered from to , going from bottom to top. Its columns are numbered from to , going from left to right. Each square is referenced by a tuple, , describing the row, , and column, , where the square is located.
The queen is standing at position . In a single move, she can attack any square in any of the eight directions (left, right, up, down, and the four diagonals). In the diagram below, the green circles denote all the cells the queen can attack from :
There are obstacles on the chessboard, each preventing the queen from attacking any square beyond it on that path. For example, an obstacle at location in the diagram above prevents the queen from attacking cells , , and :
Given the queen's position and the locations of all the obstacles, find and print the number of…
Chapter 5 Solutions
Artificial Intelligence: A Modern Approach
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.Similar questions
- onsider the challenge of determining whether a witness questioned by a law enforcement agency is telling the truth. An innovative questioning system pegs two individuals against each other. A reliable witness can determine whether the other individual is telling the truth. However, an unreliable witness's testimony is questionable, below is a confusion matrix of all the possible outcomes from a given scenarios, This pairwise approach could then be applied to a larger pool of witnesses. Answer the following: Assume a pool of K witnesses, in which the reliable ones are eager to help solve a case, and the unreliable ones are equally eager to hide the truth. Prove that if more than half of the witnesses are unreliable, the approach outlined above cannot help identifying the reliable witnesses.arrow_forwardTM M = (Q, E, I, 6, 90, 9a, qr), where Q = {90, 91, 92, 9a, 9r}, Σ = {0, 1}, r = {0, 1, L}, and 8 is: 8(qo, U) = (qr, U, R) 8(90, 0) = 8(go, 1) (91, 0, R) (qo, 1, R) = 8(g1, L) = (ga, U, R) 8(91,0) = (91, 0, R) 8(91, 1) = (92, 1, R) = (92, U, R) 8(92, U) 8(92, 0) = (90, 0, R) 8(92, 1) = (92, 1, R) i. Prove that M is NOT a decider. ii. Mathematically describe the language A that M recognises. Prove that A ≤ L(M). iii. Prove A = L(M). iv. Is A Turing-decidable? [Give clear reasons for your answer. No need for a formal proof.]arrow_forwardGiven the sets A = { A, B, C, D} and B = {C, D, E}, what is A v B A-Barrow_forward
- Dingyu is playing a game defined on an n X n board. Each cell (i, j) of the board (1 2, he may only go to (2, n).) The reward he earns for a move from cell C to cell D is |value of cell C – value of cell D|. The game ends when he reaches (n, n). The total reward - is the sum of the rewards for each move he makes. For example, if n = 1 2 and A = 3 the answer is 4 since he can visit (1, 1) → (1, 2) → (2, 2), and no other solution will get a higher reward. A. Write a recurrence relation to express the maximum possible reward Dingyu can achieve in traveling from cell (1, 1) to cell (n, n). Be sure to include any necessary base cases. B. State the asymptotic (big-O) running time, as a function of n, of a bottom-up dynamic programming algorithm based on your answer from the previous part. Briefly justify your answer. (You do not need to write down the algorithm itself.)arrow_forwardDescription Implement a Taylor series approximation of some mathematical functions. In mathematics, the Taylor series is a way of approximating transcendental functions such as sin x or log x. In this approach, we can approximate a mathematical function as closely as we might want to by adding together numbers that get us closer and closer to the true value of the function. For example, the exponential function e" can be approximated as: 73 e" = 1+x + 2! 3! - nl and the sin function can be approximated as: (-1)" 73 sin z = x - 3! „5 77 2n+1 (2n + 1)! 5! 7! n=0 The more terms we include in our approximation, the better an approximation we get of sin x. In this assignment, you must implement Taylor series approximations for these two functions. Your functions should take two parameters: the value of x and the number of terms to use in the approximation: /** * Calculate an approximate value for the exponential function. @param the value to raise e to the power of (i.e., e to the x) *…arrow_forwardA certain cat shelter has devised a novel way of making prospective adopters choose their new pet. To remove pet owners’ biases regarding breed, age, or looks, they are led blindfolded into a room containing all the cats up for adoption and must bring home whichever they pick up. Suppose you are trying to adopt two cats, and the shelter contains a total of N cats in one of only two colors: black or orange. is it still possible to pick up two black cats with probability ½, given that there is an even number of orange cats in the room? If so, how many cats should be in the room? How many black, how many orange?arrow_forward
- Correct answer will be upvoted else downvoted. Computer science. Michael is blamed for disregarding the social separating rules and making a danger of spreading Covid. He is currently shipped off jail. Fortunately, Michael knows precisely what the jail resembles from within, particularly since it's actual straightforward. The jail can be addressed as a square shape a×b which is partitioned into abdominal muscle cells, each addressing a jail cell, normal sides being the dividers among cells, and sides on the edge being the dividers prompting opportunity. Prior to condemning, Michael can ask his companions among the jail representatives to make (all around stowed away) openings in a portion of the dividers (counting dividers among cells and the furthest dividers). Michael needs to have the option to escape the jail after this, regardless of which cell he is set in. Nonetheless, he likewise needs to break as couple of dividers as could be expected. Your assignment is to discover…arrow_forwardCorrect answer will be upvoted else downvoted. Computer science. Michael is blamed for disregarding the social removing rules and making a danger of spreading Covid. He is currently shipped off jail. Fortunately, Michael knows precisely what the jail resembles from within, particularly since it's actual straightforward. The jail can be addressed as a square shape a×b which is separated into stomach muscle cells, each addressing a jail cell, normal sides being the dividers among cells, and sides on the border being the dividers prompting opportunity. Prior to condemning, Michael can ask his companions among the jail representatives to make (all around stowed away) openings in a portion of the dividers (counting dividers among cells and the furthest dividers). Michael needs to have the option to escape the jail after this, regardless of which cell he is set in. Be that as it may, he likewise needs to break as couple of dividers as could be expected. Your assignment is to…arrow_forwardBus timetables specify to the second the exact arrival and departure time of each bus on each stop. You need to pay for the full fare of every bus you ride and different bus lines charge different fees , but they are flat fees (independent of distance travelled on the line) A travel plan is a sequence of stop-time pairs where stop is a location of a bus stop and time is when we arrive at that stop. The plan is feasible if for any two consecutive pairs (a, t) and (b, t′) in the plan there exists a bus that departs after t and arrives at b at exactly t′. That is, a travel plan does not allow us to walk between stops. Assuming that no two buses arrive at the same time at the same stop, a feasible plan uniquely identifies the bus lines that we need to take to realize the plan. The cost of the plan is the sum of the fares we need to pay. Your task is to design an efficient algorithm that given a departure time t, an arrival time t′, an origin stop a and a destination stop b, finds the…arrow_forward
- Given two strings X and Y, where X consists of the sequence of symbols X1, X2, Xm and Y consists of the sequence of symbols y₁,Y2, ***,yn. Consider the sets {1, 2, ..., m} and {1, 2, ..., n} as representing the different positions in the strings X and Y, and consider a matching of these sets, where a matching is a set of ordered pairs with the property that each item occurs in at most one pair. A matching M of these two sets is an alignment if there are no "crossing" pairs: if (i,j). (i*,j') = Mandi 0 that defines a gap penalty. For each position of X or Y that is not matched in M (it is a gap), we incur a cost of 8. Second, for each pair of letters p and q (p + q) in our alphabet, there is a mismatch cost of app for lining up p with q. Thus, for each (i,j) = M, we pay the appropriate mismatch cost axiy for lining up x; with y;. The cost of M is the sum of its gap and mismatch costs, and the problem seeks an alignment of minimum cost. Define the minimum alignment cost OPT(i,j) (0 ≤ i ≤…arrow_forwardWhen faced with a difficult problem in mathematics, it often helps to draw a picture. If the problem involves a discrete collection of interrelated objects, it is natural to sketch the objects and draw lines between them to indicate the relationships. A graph (composed of dots called vertices connected by lines or curves called edges) is the mathematical version of such a sketch. The edges of a graph may have arrows on them; in this case, the graph is called a directed graph. When we draw a graph, it doesn’t really matter where we put the vertices or whether we draw the edges as curved or straight; rather, what matters is whether or not two given vertices are connected by an edge (or edges). The degree of a vertex is the number of edges incident to it (i.e., the number of times an edge touches it). This is different than the number of edges touching it, because an edge my form a loop; for instance, vertex ? in graph ? (above) has degree 5. In a directed graph, we can speak of the…arrow_forwardWhen faced with a difficult problem in mathematics, it often helps to draw a picture. If the problem involves a discrete collection of interrelated objects, it is natural to sketch the objects and draw lines between them to indicate the relationships. A graph (composed of dots called vertices connected by lines or curves called edges) is the mathematical version of such a sketch. The edges of a graph may have arrows on them; in this case, the graph is called a directed graph. When we draw a graph, it doesn’t really matter where we put the vertices or whether we draw the edges as curved or straight; rather, what matters is whether or not two given vertices are connected by an edge (or edges). The degree of a vertex is the number of edges incident to it (i.e., the number of times an edge touches it). This is different than the number of edges touching it, because an edge my form a loop; for instance, vertex ? in graph ? (above) has degree 5. In a directed graph, we can speak of the…arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Database System ConceptsComputer ScienceISBN:9780078022159Author:Abraham Silberschatz Professor, Henry F. Korth, S. SudarshanPublisher:McGraw-Hill Education
Starting Out with Python (4th Edition)Computer ScienceISBN:9780134444321Author:Tony GaddisPublisher:PEARSON
Digital Fundamentals (11th Edition)Computer ScienceISBN:9780132737968Author:Thomas L. FloydPublisher:PEARSON
C How to Program (8th Edition)Computer ScienceISBN:9780133976892Author:Paul J. Deitel, Harvey DeitelPublisher:PEARSON
Database Systems: Design, Implementation, & Manag...Computer ScienceISBN:9781337627900Author:Carlos Coronel, Steven MorrisPublisher:Cengage Learning
Programmable Logic ControllersComputer ScienceISBN:9780073373843Author:Frank D. PetruzellaPublisher:McGraw-Hill Education
Database System Concepts
Computer Science
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:McGraw-Hill Education
Starting Out with Python (4th Edition)
Computer Science
ISBN:9780134444321
Author:Tony Gaddis
Publisher:PEARSON
Digital Fundamentals (11th Edition)
Computer Science
ISBN:9780132737968
Author:Thomas L. Floyd
Publisher:PEARSON
C How to Program (8th Edition)
Computer Science
ISBN:9780133976892
Author:Paul J. Deitel, Harvey Deitel
Publisher:PEARSON
Database Systems: Design, Implementation, & Manag...
Computer Science
ISBN:9781337627900
Author:Carlos Coronel, Steven Morris
Publisher:Cengage Learning
Programmable Logic Controllers
Computer Science
ISBN:9780073373843
Author:Frank D. Petruzella
Publisher:McGraw-Hill Education