Course PM

Introduction This course gives a broad overview of the problems and methods studied in the field of artificial intelligence.

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¶ Please respect the code of honour.

Crew
* Lecturers
* Patric Jensfelt (course responsible)

* Teaching assistants (TA)
* Johannes A. Stork
* Akshaya Thippur
* Kaiyu Hang

Lectures The table below gives a rough overview of the lectures. The lecture notes will be posted in conjunction with the lecture. The exact content of each lecture is only tentative and may be adapted along the way.

The chapters refers to the course book "Artificial Intelligence: A Modern Approach" (3rd Edition) by Stuart J. Russell and Peter Norvig.

Date Content Chapters Downloads L1 Introduction Agents and search, hw+proj intro 1-2 L2 Search 3,4 lecture02 L3 Search Games 3-5 lecture03 L4 CSP 6 lecture04 L5 Probabilistic reasoning 13, 14 lecture05 L6 Bayesian Networks 13-15 lecture06probabilities_recap L7 Hidden Markov Models 1 13-15 lecture07HMM_Tutorial_MannHMM_Tutorial_Rabiner HMM_Tutorial_Stamp L8 Hidden Markov Models 2 13-15 lecture08 L9 Logic and Representation of Knowledge 10-11 lecture09 and lecture10.1 L10 Planning 7-9, 12 lecture10.2 L11 Guest lecture: Gabriel Skantze 22-23 - L12 Project Report Feedback Slides L13 Making decisions 16-17 lecture13 L14 Robotics, computer vision and machine learning 24-25 lecture14 Exercises # / Week Tutorial Title Content Downloads 1 / w36 BPT Search Admin: Kattis, portal, Hands-on: using pipes, version control, tips Tutorial Slides 2 / w37 Games Games: minimax, alpha-beta, heuristics, testing Tutorial Slides 3 / w39 HMM1 HMM: core concepts and algorithms: forward pass, backward pass, baum-welch; solving examples Tutorial Slides HMM1_Handout_QsHMM1_Handout_AsHMM1_Handout_BoltHMM1_Handout_Weather 4 / w40 HMM2 HMM: Viterbi algorithm, HMM examples, Real world HMM problems, HMM problem decomposition Tutorial Slides HMM2_Handout_QsHMM2_Handout_As 5 Ethics CANCELED Help Sessions We offer help sessions every day of the week (Mon-Fri), usually at 15:00, in room 22:an (304), at Teknikringen 14. The KTH webpage has a map that can show you the way there. On some occasions the help sessions have to be moved to a different room. To know when we change the room, read the information page about help sessions.

Examination and grading The examination consists of completing homework assignments (individual) and a projects (in groups).

To recieve a passing grade on the course a student needs to pass all home work assignment (BPT, HW1, HW2 HW3/Ethics) as well as the requirements for the project. The project has to be completed in groups.

Each homework assignment and the project will be given a numeric score which is summed up.

Max points BPT P/F HW1 25 HW2 35 HW3 P/F Project 40

The final grade, A-F, is given according to

* A: >=85
* B: >=75
* C: >=65
* D: >=55
* E: >=40
NOTE: All homework assignments and project should be completed in English

For all examinations, we use the CSC code of honour.

Homework This course gives a broad overview of the field of AI. The homeworks are intended to give the student a chance to work with the material a bit more hands-on.

There will be 2 homework assignments and an initial basic programming test handed out during the course. Please pay attention to the dates for handing them in as we will be strict with the deadlines!

There will be two deadlines for HW1 and HW2. Assignments handed in before the first deadline, the bonus deadline, are rewarded with an additional 2 points (assuming you meet the minimum requirements for the corresponding assignment). Submission after the second deadline are limited to getting a maximum of the minimum required number of points. You submit electronically (to kattis) and you are allowed to submit as many times as you want and for both deadlines if you want and the best result will count. Note that the bonus points are only added to the score on assignments handed in before the bonus deadline. That is, if you get 5 points at the first deadline and 6 points at the second you score would be 5+2=7 and not 6+2.

Please ask questions about the homeworks via this portal or at one of the help sessions.

Project The project offers you a chance to practice team work and work on a slightly larger problems that require you to work together. Being able to work in a group is an instrumental skill in most jobs both in academia and industry. You will be required to write a report, make a presentation and review another group's report and act as opponents at their presentation. The score on the project is based on all of these parts, ie not only your "end product").

The project work should be carried out in groups of 4 people. You are free to form your own groups. You define the group in the course portal. People that have not formed groups by the deadline will be assigned groups.

NOTE: You cannot be part of a group until you passed the BPT

NOTE: You will be given a deadline to form groups. If you want to be in a certain group, make sure to form the group before the deadline. If you are not a member of a team (enough if team members have invited you to be considered to be part of the team) after that deadline you have forfeited your ability to chose group and will be placed in a group.

Please ask questions about the project here or on one of the help sessions.

Consultation If you have questions or problems of organizational or formal character regarding this course, please do not contact the professor directly. Instead make use of the consultation time on Monday, 12:15 pm - 1 pm, Computer Vision and Active Perception Lab, Teknikringen 14, Plan 7, Room 721. Take the stairs to Plan 7 and ring the doorbell or call someone to send the elevator down.