Artificial Intelligence: A Modern Approach
3rd Edition
ISBN: 9780136042594
Author: Stuart Russell, Peter Norvig
Publisher: Prentice Hall
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Expert Solution & Answer
Chapter 3, Problem 20E
Explanation of Solution
a.
Vacuum world problem:
- The vacuum world problem can be solved easily using depth-first-search. In this the iterative deepening search is an enhanced version of the depth first search.
- The expansion is used by the iterative deepening search and takes the suboptimal path across nodes before reaching the target node.
- Hence the iterative deepening depth first search is the best search option...
Explanation of Solution
b.
Applying chosen
The computation of the sequence when the top three squares are dirty and agent in centre is as follows,
- Agent: The agent is having the locations of dirty places.
- Goal test: Clean each square so o dirt left in the path...
Explanation of Solution
c.
Constructing and evaluating the performance of a search agent of vacuum world:
- Consider the
- The starting location of the agent id (1,1) and it is facing towards the right.
- The agent can make the following movements – move forward, turn left, turn right, grab dirt or shoot.
- The agent will not have the forward move when the agent reaches the last square, that is when the agent is facing the wall.
- The possibility of moving to the adjacent box is 0.9 for the remaining squares.
- The probability is 0.1 if there is no change in the location. The probability is calculated by assuming that all the components remain static.
- Only the direction changes when a movement is made to turn right or to turn left. The location does not change in this case.
- The probability is 0.8 for the direction. The quarter turn which the agent makes to change the facing direction has a probability of 0
Explanation of Solution
d.
Comparison between the iterative deepening search and the simple random reflex agent:
- While comparing the iterative deepening search with simple random reflex agent, the iterative deepening search agent has the probability of 0.2 in any direction, executes the process.
- The iterative deepening search agent movement can be defined...
Explanation of Solution
e.
Performance of search agent and reflex agent with n:
For N states,
Action: right, left an...
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Students have asked these similar questions
Consider the vacuum-world problem defined as shown in the following figure.
a. Which of the algorithms defined in this chapter would be appropriate for this problem? Should the algorithm use tree search or graph search?
b. Apply your chosen algorithm to compute an optimal sequence of actions for a 3×3 world whose initial state has dirt in the three top squares and the agent in the center.
c. Will you prefer an agent with state/ memory in this scenario?
d. Compare your best search agent with a simple randomized reflex agent that sucks if there is dirt and otherwise moves randomly.
e. Consider what would happen if the world were enlarged to n × n. How does the performance of the search agent and of the reflex agent vary with n?
I need these questions solutions as soon as possible sir.
Question: Consider the vacuum-world problem defined as shown in the following figure-1.
a. Which of the algorithms defined in this chapter would be appropriate for this problem? Should the algorithm use tree search or graph search?
b. Apply your chosen algorithm to compute an optimal sequence of actions for a 3×3 world whose initial state has dirt in the three top squares and the agent in the center.
c. Construct a search agent for the vacuum world and evaluate its performance in a set of 3×3 worlds with a probability of 0.2 of dirt in each square. Include the search cost as well as path cost in the performance measure, using a reasonable exchange rate.
d. Compare your best search agent with a simple randomized reflex agent that sucks if there is dirt and otherwise moves randomly.e. Consider what would happen if the world were enlarged to n × n. How does the performance of the search agent and of the reflex agent vary with n?…
Question 9. Present an algorithm for the following problem. The input is a weighted graph G, two vertices s
and t, and a positive number k. The goal is to find a path from s to t such that all edges along the path have weight
≤ k (if there is such a path), or to print "no good path", if there is no such path.
Chapter 3 Solutions
Artificial Intelligence: A Modern Approach
Ch. 3 - Explain why problem formulation must follow goal...Ch. 3 - Prob. 2ECh. 3 - Prob. 3ECh. 3 - Prob. 4ECh. 3 - Prob. 5ECh. 3 - Prob. 6ECh. 3 - Prob. 8ECh. 3 - Prob. 9ECh. 3 - Prob. 10ECh. 3 - Prob. 11E
Ch. 3 - Prob. 12ECh. 3 - Prob. 13ECh. 3 - Prob. 14ECh. 3 - Prob. 15ECh. 3 - Prob. 16ECh. 3 - Prob. 17ECh. 3 - Prob. 18ECh. 3 - Prob. 20ECh. 3 - Prob. 21ECh. 3 - Prob. 22ECh. 3 - Trace the operation of A search applied to the...Ch. 3 - Prob. 24ECh. 3 - Prob. 25ECh. 3 - Prob. 26ECh. 3 - Prob. 27ECh. 3 - Prob. 28ECh. 3 - Prob. 29ECh. 3 - Prob. 31ECh. 3 - Prob. 32E
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