Course Syllabus

Artificial Intelligence

 

Semester & Location:	Fall 2019- DIS Copenhagen
Type & Credits:	Elective Course - 3 credits
Major Disciplines:	Computer Science. Mathematics
Faculty Members:	Thomas Bolander, tobo@dtu.dk
Program Director:	Iben de Neergaard, idn@dis.dk
Time & Place:	Mondays, 13.15-16.10 Location: V10-A22

Course Description

Artificial Intelligence (AI) is behind your smart phone’s intelligent personal assistant, driverless cars, robots, government fraud detection systems, and the image recognition algorithms of Facebook and Instagram, just to mention a few examples.  This course introduces you to core techniques and applications of Artificial Intelligence using primarily symbolic methods in an agent-oriented paradigm.

Classes are a mix of discussions of theory/core concepts and hands-on problem solving. The majority of the course work is carried out in groups.

During the course, you will implement simple search-based agents solving transportation tasks in a virtual environment. The virtual environment is an idealized model of systems of delivery robots in hospitals, the warehouse robots at Amazon, etc. This part of the course is referred to as the programming project.

The course consists of the following parts:

1. Introduction to AI (foundations of AI + intelligent agents). 2 sessions.
2. The philosophy, ethics and future of AI. 2 sessions + group presentations throughout the course (critical review).
3. Problem-solving by searching: uninformed and informed search. This part covers the background material for the programming project assignment. 4 sessions.
4. Lab work on the programming project. 8 sessions.
5. Machine learning: Neural networks and reinforcement learning. A short crash course in important machine learning techniques. 2 sessions.
6. Game playing and adversarial search.  This part covers the background material for the AI in board games assignment. 2 sessions. 
7. Lab work on AI in board games. 2 sessions. 

Course Themes

1. Foundations of AI
2. Intelligent agents
3. Problem-solving by searching
4. Adversarial search (games)
5. Neural networks and reinforcement learning
6. Applications of AI
7. Philosophy, ethics and future of AI

 

Learning Outcomes

Upon successfully completing this course, you will be able to:

• Correctly determine which AI technique(s) should be used to solve a particular problem - if any
• Design software agents that act rationally in complex domains
• Design formal problems in AI and identify important features and properties
• Explain concisely the scope of AI, its potential for society as well as its limitations
• Discuss contemporary applications of AI from both a technical and an ethical perspective

 

Prerequisites

One year of introduction to computer science and a semester of calculus at university level. It is strongly recommended that you have had an introduction to data structures and algorithms, mathematical modeling and imperative programming.

Faculty

Thomas Bolander, Ph.D., is an associate professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). His research areas are logic and artificial intelligence, focusing primarily on the use of logic to model human-like planning, reasoning and problem solving. Of special interest is the modeling of social phenomena and social intelligence with the aim of creating computer systems that can interact intelligently with humans and other computer systems. The application areas of interest are e.g. computer-controlled characters in computer games, intelligent personal assistants in mobile phones, and mobile robots. 

Thomas Bolander has developed and taught a wide range of courses in mathematics, computer science and artificial intelligence. In 2006, he received the "teacher of the year" award at DTU, and in 2019 the H. C. Ørsted Silver Medal for excellence in science communication. In the period 2009-2013 he was director of studies at the Copenhagen University Extension, and 2011-2014 part-time employed as educational developer at LearningLab DTU, taking part in developing and teaching the Education in University Teaching at DTU. Thomas Bolander is a member of several commissions and think tanks discussing the future of AI, its ethical aspects and societal impact. He is furthermore co-organiser and scientific advisor for Science & Cocktails, award-winning organiser of popular science events.

 

Textbook

Stuart Russell and Peter Norvig: Artificial Intelligence - A Modern Approach. 3rd ed., global edition, Pearson, 2014.

All readings in the Course Summary below refer to this textbook unless otherwise noted. 

 

Assignments and Evaluation

More details will be provided by your instructor in class.

• Assignment: Programming project (40%). The project is divided into two parts, each accounting for 20% of the final grade.  
• Assignment: AI in board games (20%).
• Presentation: critical review of a mainstream media article on the philosophy/ethics/future of AI (15%).
• Final exam: A final written exam with exercises similar to the ones provided during classes (25%).

The two assignments and the presentation are group work. Only the final exam is individual. 

General note regarding assignments

Papers should be correctly formatted and referenced. Double-spaced. Times New Roman. 12-point font. 1-inch margins. At DIS, one page equals 300 words. Papers not adhering to these guidelines will result in point deductions. Late assignments will be deducted a third of a grade point per day it is late. All work must be handed in in order to get a passing grade.

 

Attendance        

You are expected to attend all DIS classes when scheduled. All classes, events and field trips are mandatory unless marked otherwise in the course plan. If you miss multiple classes, the Director of Academic Support and the Director of Student Affairs will be notified. Absences will jeopardize your grade and your standing at DIS.  Allowances will be made in cases of illness, but in the case of multiple absences, you will need to provide a doctor’s note.

 

Field Studies May Include

• Board game playing
• Visit to the AI and robotics facilities at the Technical University of Denmark (DTU)
• Visit to CIBS – Center for Information and Bubble Studies, University of Copenhagen (KU)
• Visit to IBM including exercises on IBM chatbot technology
• Visit to LEO Innovation Lab developing AI-based health apps