Artificial Intelligence: A Modern Approach
3rd Edition
ISBN: 9780136042594
Author: Stuart Russell, Peter Norvig
Publisher: Prentice Hall
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Chapter 5, Problem 11E
a.
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Move generators and evaluation function
- Evaluation functions are algorithms that sele...
b.
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Alpha-beta game playing event
- Alpha beta game playing environment is a...
c.
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Effect of increasing search depth
- Without an evaluation function and truncated horizon, depth and ordering cannot be scaled up...
d.
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Selective search
- It is used in object detection.
- It is a fast algorithm with high recall...
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Implement an algorithmic solution, indicating which states are valid and which are not, and model the space of the following problem:
An interest group from a small town decided to sue a company for commercial abuse. For this, the people have organized themselves and decided to send 3 representatives, who will have to travel in a Van to the city where the lawsuit will be filed. The company to be sued, upon learning of these actions, has decided to send 3 lawyers to persuade the representatives, who will also travel in the same Van for that purpose.
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The wolf-goat-cabbage ProblemDescription of the problem: There is a farmer who wishes to cross a river but he is not alone. He also has a goat, a wolf, and a cabbage along with him. There is only one boat available which can support the farmer and either of the goat, wolf or the cabbage. So at a time, the boat can have only two objects (farmer and one other).
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This problem exercises the basic concepts of game playing, using tic-tac-toe (noughtsand crosses) as an example. We define Xn as the number of rows, columns, or diagonals with exactly n X’s and no O’s. Similarly, On is the number of rows, columns, or diagonals with just n O’s. The utility function assigns +1 to any position with X3 = 1 and −1 to any position with O3 = 1. All other terminal positions have utility 0. For nonterminal positions, we use a linear evaluation function defined as Eval (s) = 3X2(s)+X1(s)−(3O2(s)+O1(s))."Mark on your tree the evaluations of all the positions at depth 2."
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Artificial Intelligence: A Modern Approach
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- Using c++ Apply both breadth-first search and best-first search to a modified version of MC problem. In the modified MC, a state can contain any number of M’s and any number of C’s on either side of the river. Assume the goal is always to move all the persons on the left side to the right side. The Initial state should be a parameter given to the program at beginning of execution. As in the original problem, boat capacity =2, the boat cannot move by itself, and on either side C’s should not outnumber M’s. For best-first search, you need to come up with an appropriate heuristic. In addition to solving the problem, your grade will also be based on th effectiveness of the heuristic. As an example, the program should execute as follows. Initial state… Enter number of M’s on left side of the river: 3 Enter number of C’s on left side of the river: 1 Enter number of M’s on right side of the river: 0 Enter number of C’s on right side of the river: 0 Enter location of the boat: L The output…arrow_forwardPlease answer the following question in depth with full detail. Consider the 8-puzzle that we discussed in class. Suppose we define a new heuristic function h3 which is the average of h1 and h2, and another heuristic function h4 which is the sum of h1 and h2. That is, for every state s ∈ S: h3(s) =h1(s) + h2(s) 2 h4(s) =h1(s) + h2(s) where h1 and h2 are defined as “the number of misplaced tiles”, and “the sum of the distances of the tiles from their goal positions”, respectively. Are h3 and h4 admissible? If admissible, compare their dominance with respect to h1 and h2, if not, provide a counterexample, i.e. a puzzle configuration where dominance does not hold.arrow_forward1. Following question _Qestion 2 – Simple Machine-Learning Function Java Program A Learning Function is an empirical formula which isresponsible for regulating the training of an agentwith respect to Machine Learning and Artificial Intelligence (AI). In this regard, given below is ourprototype Learning Function, ?, which tunes and regulates the training as well as learning in our AIagents. This is defined such that: ? = ? ∗ ΩGiven that Ω = 0.567143 and ? is a dynamic variable, which is defined with respect to the day ofthe week and the time of the day, as illustrated in the table below: Weekday/Time Day-Light Night-Time Monday 2.53 3.25 Tuesday 3.15 2.99 Wednesday 3.00 3.99 Thursday 2.41 2.68 Friday 1.99 3.73 Saturday 3.59 2.86 Sunday 2.00 2.59 Therefore, write a Java class/program correctly such that your source code will accomplish the following: 1. Display a prompt message for the user to enter the Weekday and the Time as a single input separated via the space…arrow_forward
- Answer the following: This problem exercises the basic concepts of game playing, using tic-tac-toe (noughts and crosses) as an example. We define Xn as the number of rows, columns, or diagonals with exactly n X’s and no O’s. Similarly, On is the number of rows, columns, or diagonals with just n O’s. The utility function assigns +1 to any position with X3=1 and −1 to any position with O3=1. All other terminal positions have utility 0. For nonterminal positions, we use a linear evaluation function defined as Eval(s)=3X2(s)+X1(s)−(3O2(s)+O1(s)). a. Show the whole game tree starting from an empty board down to depth 2 (i.e., one X and one O on the board), taking symmetry into account. b. Mark on your tree the evaluations of all the positions at depth 2. c .Using the minimax algorithm, mark on your tree the backed-up values for the positions at depths 1 and 0, and use those values to choose the best starting move. Provide original solution!arrow_forwardCreate a curve that uses a quadratic parametric approach with three interpolated control points. The equations which describe the curve are: $$f_x(u) = c_0 u^2 + c_1 u + c_2 $$ and $$f_y(u) = c_3 u^2 + c_4 u + c_5 $$ where $u$ ranges from 0.0 to 1.0. The first control point $$p_0$$ is for $u=0$, the second $p_1$ for $u=0.5$, and the third for $p_2$ and at $u=1.0$. Modify the code to implement your solution. It is sufficient for this task to get the program working with three control points, but you are most welcome to attempt a solution that works on four or more. Code: import java.awt.Graphics2D; import java.awt.geom.Ellipse2D; import java.awt.geom.Path2D; import java.awt.geom.Point2D; import javax.swing.JFrame; import javax.swing.JTabbedPane; import javax.swing.SwingUtilities; public class DotToDotDemo implements Runnable { /** * DotToDotDemo - A demo which draws dots between points to form a curve. * Eric McCreath 2015, 2019 - GPL * Modified by Matthew Aitchison 2022. */ JFrame…arrow_forwardConsider the following set of training examples: (a) What is the entropy of this collection of training examples with respect to the target function classification? (b) What is the information gain of az relative.to these training examples?arrow_forward
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