Critically discuss the particular determinants of demand for Toyota Motor Corporation Global benchmarking them against the theory. The determinants include: - Price, Income, Prices of Related Products,...4. Assessment on this module4.1.1 Element 010– ASSIGNMENT 3000 WORDS (100%)Element Type of assessment Word ortime limit % of Total Mark Submission method Final Submission Date010 ASSIGNMENT 3000 WORDS...ASSESSMENT BRIEFSubject Code and Title ACCT6007 Financial Accounting Theory and PracticeAssessment Critical AnalysisIndividual/Group IndividualLength 1500 words +/- 10%Learning Outcomes 1. Identify the...Unit 4 QuestionsST. MARY'S CATHOLIC COLLEGEProviding excellence in Education since 1986YEAR 12 AUTHORITY ENGLISHTASK 1: PUBLIC PERSUASIVE SPEECHUNIT 1: VOICES FROM THE PASTNAME: M(1-1,q),e, Vat-) Oe,r Krr,00 CLASS:...Key AssignmentUtilizing any available disclosed database for SPSS, develop a researchable set of hypotheses related to the database. Clearly define quantitatively analyzable hypotheses, analyze your data...Unit Quiz and Unit Homework as attached**Show All Questions**

Part 1 Text Reading:

• Introduction to Artificial Intelligence (Chap. 1)

• Intelligent Agents (Chap. 2)

• Searching (Chaps. 3, 4)

Part 2 Problems:

• 2.1 Depth-first and breadth-first search

Figure 1

1. Apply the BFS algorithm and show the output

2. Apply the DFS algorithm and show the output

3. Show the output from the previous question in the form of a DFS tree

2.2 A* Algorithm Search

1. Suppose the state space consists of all possible positions (x, y) in the plane. How many states are there? How many paths are there to the goal? (There might be different answers to this question. Your answer should be based on a reasonable assumption and the assumptions should be explicitly shown in your submission.)

2. Based on the above observation, define a good state space for the problem. How large is the state space? Why?

3. Implement an algorithm to find the shortest path from the start node to the end node using an A* heuristic search. Use the straight-line distance to the end node as a heuristic function. Show your pseudo code (not your source code) for this algorithm. In addition you need to answer the following question: is this an admissible heuristic function? Why or why not?

4. Explicitly present the solutions for the following problem using the A* algorithm you implemented.

5. Is it possible to solve the problem using a breadth-first or a depth-first search algorithm? If the answer is yes, briefly discuss your solutions. Otherwise please explain.

• Introduction to Artificial Intelligence (Chap. 1)

• Intelligent Agents (Chap. 2)

• Searching (Chaps. 3, 4)

Part 2 Problems:

• 2.1 Depth-first and breadth-first search

Figure 1

1. Apply the BFS algorithm and show the output

2. Apply the DFS algorithm and show the output

3. Show the output from the previous question in the form of a DFS tree

2.2 A* Algorithm Search

1. Suppose the state space consists of all possible positions (x, y) in the plane. How many states are there? How many paths are there to the goal? (There might be different answers to this question. Your answer should be based on a reasonable assumption and the assumptions should be explicitly shown in your submission.)

2. Based on the above observation, define a good state space for the problem. How large is the state space? Why?

3. Implement an algorithm to find the shortest path from the start node to the end node using an A* heuristic search. Use the straight-line distance to the end node as a heuristic function. Show your pseudo code (not your source code) for this algorithm. In addition you need to answer the following question: is this an admissible heuristic function? Why or why not?

4. Explicitly present the solutions for the following problem using the A* algorithm you implemented.

5. Is it possible to solve the problem using a breadth-first or a depth-first search algorithm? If the answer is yes, briefly discuss your solutions. Otherwise please explain.