ECTS - Advanced Artificial Intelligence
Advanced Artificial Intelligence (MDES677) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Advanced Artificial Intelligence | MDES677 | Elective Courses | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses Taken From Other Departments |
| Course Level | Ph.D. |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| Course Objectives | To introduce advanced concepts and different approaches to Artificial Intelligence (AI) (including symbolic and non-symbolic ones). To extent the engineering vision of the student. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Intelligent agents, problem solving by searching, informed/uninformed search methods, exploration, constraint satisfaction problems, game playing, knowledge and reasoning: first-order logic, knowledge representation, learning, selected topics: evolutionary computing, multiagent systems, artificial neural networks, ant colony optimization. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Intelligent Agents | Chapters 1-2 from Russell & Norvig |
| 2 | Intelligent Agents | Chapter 1-2 from Russell & Norvig |
| 3 | Informed/Uninformed Search Methods, Exploration | Chapter 3-4 from Russell & Norvig |
| 4 | Informed/Uninformed Search Methods, Exploration | Chapter 3-4 from Russell & Norvig |
| 5 | Constraint Satisfaction Problems | Chapter 5 from Russell & Norvig |
| 6 | Constraint Satisfaction Problems | Chapter 5 from Russell & Norvig |
| 7 | Game Playing | Chapter 6 from Russell & Norvig |
| 8 | Knowledge and Reasoning : Logical Agents | Chapter 7 from Russell & Norvig |
| 9 | Knowledge and Reasoning : First-Order Logic | Chapter 8 from Russell & Norvig |
| 10 | Knowledge and Reasoning : Inference in First-Order Logic | Chapter 9 from Russell & Norvig |
| 11 | Selected Topics : Evolutionary Computing | Source #5 |
| 12 | Selected Topics : Multiagent Systems | Source #4 |
| 13 | Selected Topics : Neural Networks | Source #3 |
| 14 | Selected Topics : At Colony Optimization | Source #1 |
| 15 | Overall review | - |
| 16 | Final exam | - |
Sources
| Course Book | 1. Artificial Intelligence: A Modern Approach (Second Edition). Stuart Russell and Peter Norvig, Prentice-Hall, 2003, ISBN: 0-13-790395 |
|---|---|
| Other Sources | 2. Ant Colony Optimization, Marco Dorigo and Thomas Stützle, MIT Press, 2004. |
| 3. Artificial Intelligence, Patrick H. Winston, Addison-Wesley, 1992. | |
| 4. Introduction to the Theory of Neural Computation, J. Hertz, A. Krogh and R.G. Palmer, Addison-Wesley Publishing Company, 1991 | |
| 5. An Introduction to MultiAgent Systems, Wooldridge, M., John Wiley & Sons, 2002 | |
| 6. An Introduction to Genetic Algorithms, Melanie Mitchell, MIT Press, 1998 |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | 1 | 10 |
| Project | 1 | 25 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 25 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 4 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | |
|---|---|
| Major Area Courses | X |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Demonstrates the ability to conduct advanced research activities both individually and as a team member. | |||||
| 2 | Gains the competence to examine, evaluate, and interpret research topics through scientific reasoning. | |||||
| 3 | Develops new methods and applies them to original research areas and topics. | |||||
| 4 | Systematically acquires experimental and/or analytical data, discusses and evaluates them to reach scientific conclusions. | |||||
| 5 | Applies the scientific philosophical approach in the analysis, modeling, and design of engineering systems. | |||||
| 6 | Synthesizes knowledge in their field to create, maintain, complete, and present original studies at an international level. | |||||
| 7 | Contributes to scientific and technological advancements in their engineering field. | |||||
| 8 | Contributes to industrial and scientific progress to improve society through research activities. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 2 | 32 |
| Presentation/Seminar Prepration | 3 | 5 | 15 |
| Project | 1 | 20 | 20 |
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 8 | 8 |
| Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
| Total Workload | 133 | ||