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Chris Lewis
May 6, 2022
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CONCEPTS IN ARTIFICIAL INTELLIGENCE CAI104

Group 2387CONCEPTS IN ARTIFICIAL INTELLIGENCE CAI104

SUBJECT CODE – CAI104
SUBJECT NAME – CONCEPTS IN ARTIFICIAL INTELLIGENCE
UNIVERSITY NAME – TORRENS UNIVERSITY, AUSTRALIA

Concepts in Artificial Intelligence CAI104 assignment help

This is a major subject that is offered by Torrens University, Australia to the students who are pursuing either Bachelor of Software Engineering or Master of Software Engineering degree.

The subject will give undergraduate and graduate students the opportunity to develop and enhance their technical abilities as well as soft skills which are required to have a successful career in Artificial Intelligence. The main objective of the subject is to familiarize students with basic concepts of AI and the problems solved by AI.

The subject Concepts in Artificial Intelligence CAI104 covers a wide range of topics focusing on AI- from natural language processing to robotics. The content includes major concepts such as the Main areas of AI- Search, Logic, and Learning, basic search, heuristic search, adversarial search, constraint satisfaction, logical agents, logic and inference, knowledge representation, probabilistic reasoning, knowledge in learning, learning probabilistic methods for uncertain reasoning, reinforcement learning, and ethics of AI.
With the help of this subject, you will be able to identify and solve complex Artificial Intelligence software engineering problems and will be able to develop the required skills that are increasingly the mainstay of software engineering.

Future Career Prospects After learning about Concepts in Artificial Intelligence CAI104

Artificial Intelligence has become a quite popular subject among students these days, that is the reason why a number of International Universities are offering this subject. AI is increasing at a great speed and is present almost everywhere, even in places we may not realize. From music to healthcare and home appliances, the power of Al I is far-reaching. Therefore, in today’s smart and digital world, there is a lot of scope in this field and number of job opportunities for students. Students who are commencing with this subject have a number of career opportunities to showcase and utilize their skills and learnings. List of career paths in Artificial Intelligence-

AI Engineer

Software Engineer

Natural Language Processing

Researcher

Quisque sollicitudin augue eget pretium mattis.

Data Mining and Analysis

Machine Learning Engineer and many other paths.

What is Artificial Intelligence?

Artificial Intelligence is also known as AI and is a field of computer science that deals with Machine Learning. The main objective of AI is to make machines intelligent and solve problems the same as humans. AI is all about Learning, Thinking, Searching, Designing, and Storing things to recognize and identify the patterns. The machine must learn through experiences and mistakes.
A machine will be called Artificial Intelligence if it holds all the characteristics of human beings and behaves and solve problems just like human beings.

Problem Solving Methods in Artificial Intelligence

AI has the advantage of solving problems due to its effective methods solving problems.

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Techniques used in AI to solve problems-

Heuristics

The heuristic method aids in the understanding of a problem and the development of a solution based only on experiments and trial and error techniques. These heuristics, on the other hand, do not always deliver the best optimal solution to a particular situation. Instead, these unquestionably provide effective answers for achieving immediate objectives. As a result, when traditional methods fail to provide an effective solution to a problem, developers turn to them. Heuristics are used with optimization algorithms to improve efficiency because they only provide time-efficient solutions at the expense of accuracy.

Searching Algorithms

In AI, searching is one of the most important approaches to solving any problem. These searching algorithms are used by rational agents or problem-solving agents to locate optimal solutions. These problem-solving agents frequently use atomic representation and are goal-oriented. Furthermore, based on the quality of the solution they supply, these searching algorithms have features such as completeness, optimality, time complexity, and space complexity.

Types of Searching Algorithms-

Informed Search

Uninformed Search

Why take Concepts In Artificial Intelligence CAI104 Assignment help?

A student must put a lot of effort and practice to complete their university assignments on time and with correct solutions.
Artificial Intelligence is quite a vast field that requires a thorough understanding of the subject to score decent grades.
The professor assigns assignments to students in order to measure their level of understanding of the topic. Hence, it is observed that many students find it difficult and time-consuming to complete their assignments.

Following are some reasons why students want professional assistance for their Concepts in Artificial Intelligence CAI104 assignment-

⦁ AI is a very descriptive and technical subject in which a student needs a thorough understanding of various programming languages, hence it becomes quite stressful for them to complete their assignment on time.
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⦁ For any student to complete artificial intelligence assignment, he needs a basic understanding of python and machine learning. If the concepts are not clear, then the student should take the Concepts in Artificial Intelligence assignment help from professional writers. Our writers are well qualified in their subject and can cater to you with the best assignment help services.

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Assessment Details

Assessment1 – Theory Test (Quiz) CAI104

This is an Individual assignment and every individual would be given 50minutes to undertake the exam. With this assessment, you should demonstrate your understanding of AI history and theories as well as the ability to tackle and solve challenging problems using AI search methods. The assessment is intended to test:

Your understanding of the histories and theories covered in Modules 1 to 3.

Your ability to analyze and evaluate different uninformed search methods.

Your ability to analyze and evaluate different informed search methods.

Your understanding of optimization problems and algorithms.

Instructions-

You only have one attempt at the quiz.

This quiz is made up of 25 questions.

You will have 50 minutes to complete the quiz.

If you leave the quiz for a period of time prior to completion, there will be a forced completion.

Your quiz answers will be recorded automatically and your grade will be generated on completion.

The final grade will be 25% of your overall grade.

Assessment2 – Theory Test 2 CAI104

In this assessment, you will be given a workbook that includes a set of questions to complete. You have to answer and show your work for the questions in the workbook. This assessment should be done individually.
With this assessment, you demonstrate your ability to tackle and solve several case studies using AI search methods, knowledge representation techniques, AI theories, logic, and reasoning approaches that you have learned throughout Modules 1-8.

Question1 – Use the search methods indicated below (1.1 – 1.5), to traverse the following state space tree (30%):
1.1 Breadth-first search
1.2 Depth-first search
1.3 Iterative deepening depth-first search
1.4 Greedy best-first search
1.5 A*

CAI104 -1

Question 2 – First fill out the following truth table, which will be your reference for the main parts of this question (30%):


Prove the following expressions using truth tables:

2.1 (p q) ∧ (p r) p (q ∧ r)

2.2 (p ∨ q) ∧ (p ∨ q) q

2.3 A = { p q,
q p,
p q }
C = p q

2.4 A = { q r,
q p,
(r p) }
C = p
Write a paragraph discussing the potential applications of logic. Give a real example in which the above variables (A, C, p, q, and r) can be replaced with real-world activities.

Question 3 – Translate the following sentences into first-order logic (just translate, no verification required for this question) (20%):
3.1 All scientists are smart.
3.2 There exists a smart scientist.
3.3 No scientist loves politics
3.4 Every scientist who publishes articles also publishes books

Question 4 – Translate the following expressions into logic. Then, verify whether the following
sentences and reasoning are valid (20%):
4.1 “If I’ll go to the university then I’ll take a taxi, or if I’ll take a taxi then I’ll go to the university”.
4.2 It is not true that Alex bought a car, or if he bought a car then he had money. Therefore Alex didn’t have money.
Upon the completion of questions 4.1 and 4.2, please write a paragraph discussing the potential applications of reasoning.

Assessment3 – Project CAI104
In this assessment, you are to program an AI agent to solve a real-world, challenging case study. This assessment is done individually and you are to submit programs and supporting documents.
You are to create a robot path planner that is able to find an optimal path to navigate an
environment and reach a target. By completing this assessment, you will show your skills in
leveraging the best AI methods to solve a simplified real-world problem.

The maze can be seen in the image below. It can be seen that there are 12 rows and 24 columns, meaning there is a total of 288 blocks on the map. There are four different types of blocks in this map as follows:
• Green: wall
• White: space (void)
• Red: initial position of the robot
• Blue: the target

CAI104 -2

Instructions –
⦁ Write a reflective report detailing the experience of the development process.
The report should be 2000 words (10%+-) in length and include the following sections:
• Overview
• What went right
• What went wrong
• What you are not sure about
• Conclusion
⦁ Appropriate, effective, and correct usage of pseudocode to design and develop and
algorithm
⦁ Effective use of search and or optimization algorithms in AI.
⦁ Good selection of search and/or optimization algorithms.

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