Course Syllabus

Artificial Intelligence

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. The philosophy, ethics and future of AI. 
3. Problem-solving by searching: uninformed and informed search. 
4. Lab work on the programming project. 
5. Machine learning: Neural networks and/or reinforcement learning. Only briefly covered.
6. Game playing and adversarial search. 
7. Lab work on AI in board games.

Course Themes

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

Learning Objectives

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

Faculty

Francesco Nespoli 

Francesco Nespoli holds a PhD, Electrical and Electronic Engineering, Imperial College London 2024. Previous jobs include Research Scientist Nuance Communications UK, 2021-2023. Research Scientist, Microsoft. With DIS since January 2024

Readings

Stuart Russell and Peter Norvig: Artificial Intelligence - A Modern Approach. 

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

Field Studies:

• Hands on coding lab on Large Language Models and Voice Technology
•  Visit to the Tekniska Museum (https://www.tekniskamuseet.se/)

Expectations of the Students      

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.

Evaluation and Grading

More details will be provided by your instructor in class.

The assignments and the presentation are group work. 

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.