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CSCI 5260 Lab 2 Uninformed and Informed Search solved

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Artificial Intelligence Page 1
Overview
You may want to review the code for search.py, in the aima-python repository for additional context.
Code Exploration
• Download the search_examples.py file from the D2L dropbox. This requires the following Python libraries
(some of which you may need to install using pip install).
1. os
2. math
3. numpy
4. time
5. collections à deque
6. copy à deepcopy
7. operator à itemgetter
Search Space and Environment
• Run the program and then answer the following questions:
1. What is the search space for this problem as-is? Be sure to include the following:
§ Initial State
§ Actions
§ Transition Model
2. Give a PEAS description for the searching agents in this example. Be sure to note any differences
based on the algorithm. Performance Measure, Environment, Actuators, Sensors
3. Give an environmental description of the searching agents in this example. Include the following:
§ Observability – Fully or Partially
§ Agent Type – Single or Multi
§ Deterministic or Stochastic
§ Episodic or Sequential
§ Static or Dynamic
§ Discrete or Conditinuous
§ Known or Unknown
Code Description and Performance
4. Describe the meaning of each character on the screen. What is a “.”, a “C”, an “X” and a “_”?
5. List the algorithms and the conditions used to run each, and then run each algorithm and record the
runtime for each in your writeup document.
6. Which search algorithm performs best, and under which circumstances (e.g., when diagonals are
allowed or not)? Which performs the worst? Why?
CSCI 5260 – Artificial Intelligence Page 2
Updated Code
7. Alter the code to add a series of obstacles into the field of dots. Use asterisk characters to denote an
obstacle. Each algorithm will need to avoid these obstacles, but still reach the goal.
8. List the algorithms and the conditions used to run each, and then run each and record runtimes in
your writeup document.
9. Given your obstacles, document any observations that introducing the obstacles caused in the
particular search algorithm. How did the behavior change?
Submission
Create a Word Document named SurnameLab2.docx with your responses above.
Submit your altered code in file search_examples.py.
Submit to the Lab 2 dropbox at or before Monday, February 1, by 11:59 PM.
Grading
A letter grade will be assigned for each response. The letter grades are based on both correctness and the
adequacy of answers. Points are assigned as follows:
A B C D F Zero
Excellent Above
Average Average Below
Average Poor No Attempt
10 8 6 4 2 0
Search
Space and
Environment
Q1
Q2
Q3
Code Desc.
&
Performance
Q4
Q5
Q6
Updated
Code
Q7
Q8
Q9