BSc: Introduction To Artificial Intelligence

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Introduction to Artificial Intelligence

  • Course name: Introduction to Artificial Intelligence
  • Code discipline: ?????
  • Subject area:

Short Description

This course covers the following concepts: Artificial Intelligence: Introduction to the ethical use of AI and the framework of development of AI systems; Artificial Intelligence: Evolutionary Algorithms.

Prerequisites

Prerequisite subjects

Prerequisite topics

Course Topics

Course Sections and Topics
Section Topics within the section
History and Philosophy of AI
  1. Introduction to the practical applications of AI
  2. History of Epistemology, particularly on the issue of knowledge creation and intelligence.
  3. Understanding of the Chinese room and Turing test
  4. Appreciation for the role of AI in Industries and the the application
  5. Application of the PEAS model
  6. Application of the Thinking/Acting Humanly/Rationally
  7. Appreciation of the Ethical Issues in AI
Title 2
  1. Searching Algorithms
  2. Tree Searches and logic, including basics of PROLOG as a lanuage for answering such problems
  3. First and Second order logic
Topics in Evolutionary Algorithms
  1. Understanding of the four base Evolutionary Algorithms: GA, GP, ES, EP
  2. Application of one of these four.
  3. Analysis of the application of these four types to a number of problem instances.
  4. Application of the appropriate statistical models and scientific method (i.e. Hypothesis testing) to evaluate the EA.

Intended Learning Outcomes (ILOs)

What is the main purpose of this course?

Have you ever wondered about how computers decide on what your credit worthiness is, or how they can play chess as good as a world master, or how world class circuits can be built with a minimal number of crossed wires? Perhaps you have wanted to build a human like robot, or have wanted to explore the stars with automated probes. Artificial Intelligence is the field which examines such problems. The goal is to provide a diverse theoretical overview of historical and current thought in the realm of Artificial Intelligence, Computational Intelligence, Robotics and Machine Learning Techniques.

ILOs defined at three levels

Level 1: What concepts should a student know/remember/explain?

By the end of the course, the students should be able to ...

  • Gather an appreciation of the history of AI founders
  • Solve simple problems using random, guided, and directed, search methods and be able to compare their abilities to solve the problem using a statistical argument

Level 2: What basic practical skills should a student be able to perform?

By the end of the course, the students should be able to ...

  • Understand the PEAS model of problem definition
  • Understand the Environment Model
  • Understand the role of AI within computer science in a variety of fields and applications

Level 3: What complex comprehensive skills should a student be able to apply in real-life scenarios?

By the end of the course, the students should be able to ...

  • Apply Evolutionary Algorithms to a number of problems
  • Apply the PEAS model of problem definition
  • Apply the apply the Environment Model

Grading

Course grading range

Grade Range Description of performance
A. Excellent 90-100 -
B. Good 75-89 -
C. Satisfactory 60-74 -
D. Poor 0-59 -

Course activities and grading breakdown

Activity Type Percentage of the overall course grade
Assignment 1 20
Assignment 2 20
Lab Participation 10
Midterm 25
Final 25

Recommendations for students on how to succeed in the course

Resources, literature and reference materials

Open access resources

  • Russell & Norvig - Artificial Intelligence: A Modern Approach, 3rd Edition
  • Ashlock - Evolutionary Computation for Modeling and Optimization

Closed access resources

Software and tools used within the course

Teaching Methodology: Methods, techniques, & activities

Activities and Teaching Methods

Activities within each section
Learning Activities Section 1 Section 2 Section 3
Homework and group projects 1 1 1
Midterm evaluation 1 1 0
Essays 1 0 0
Discussions 1 1 1
Development of individual parts of software product code 0 1 1
Testing (written or computer based) 0 1 1

Formative Assessment and Course Activities

Ongoing performance assessment

Section 1

Activity Type Content Is Graded?
Question State and apply the PEAS model to a set of problems. 1
Question State the difference between Plato and Aristotle’s conceptions of knowledge - refer to Socrates definition? 1
Question Are you intelligent? What marks you as such? What is the definition? 1
Question Are you creative? What marks you as such? What is the definition? 1
Question Apply the PEAS model as a group to a real world instance. 0
Question Discuss - Humans in many low skilled tasks are being replaced by automation, what role do practitioners have in protecting its abuse 0
Question Discuss - Asimov’s laws of robotics are used as a science fiction application of ethics in AI, do you think they have a role in the real world. 0
Question Discuss - how can we prevent bias from entering into systems. 0
Question Discuss - What does it mean for a Computer to be Creative? 0

Section 2

Activity Type Content Is Graded?
Question Apply Prolog to an example of a family tree 1
Question Apply Prolog to an example of a logic problem 1
Question Compare and Contrast between two different search algorithms shown in class and implement. 1
Question Given an example data set which search would you use and why? 1
Question How does Prolog implement a tree? 0
Question Does this program work - mark out any errors. 0
Question What is the difference between a red and green cut? 0
Question What is the result of this Query? 0
Question What is the time complexity of this algorithm? 0

Section 3

Activity Type Content Is Graded?
Question Define a particular EA by its data structure 1
Question Implement an EA, write a Report about the implementation with sufficient search of the parameter space justified by statistical evaluations 1
Question Analysis of two EA types base upon their representation and variation operators and suitability to a problem space. 1
Question Produce a new type of EA based upon the concepts seen in class and speculate as to its effectivenesss on a problem via hypothesis testing. 1
Question Labs within this section are primarily for supporting assistance with the above objectives, e.g. work periods with TA assistance. 0

Final assessment

Section 1

  1. Apply the PEAS model to a real world instance.
  2. You have a classification problem involving images, from the perspective of Plato and Aristotle on knowledge, which algorithm would they implement, justify your decision.
  3. Write a short essay based upon either the prosecution or defense of a trial of an Android who has passed the Turing test who is petitioning the court for human rights. What would be your case for or against using concepts in class such as Turing test, Chinese room, etc.?

Section 2

  1. Here is an example family tree. Given a simple Prolog Query - what would be the result?
  2. Here is an example logic problem. Given a Prolog Query - what would be the result.
  3. Compare and Contrast two different search algorithms in terms of time and space complexity
  4. Given data of type X, what search algorithm should you use and why?

Section 3

  1. Show an analysis on a problem instance as to which EA method you would use, justify your answer based on the representation of the problem data.
  2. Implement an EA for a problem, show statistical justification of your result.
  3. Produce a report about a new creation of an EA system with sufficient justification with hypothesis tests.

The retake exam

Section 1

Section 2

Section 3

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