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TDDC17 Artificial Intelligence

TDDC17-Lab Assistance


There are thirteen supervised lab sessions scheduled for the course this year. Lab sessions will take place physically in computer rooms at LiU campus. Below you will find the information about registration/working on/and submission of lab results.

Registration and Microsoft Teams

Registration for the labs should be done using the Web-Reg on-line registration system.

Due to the high number of students participating in the course this year single-person lab groups are not allowed - i.e. each group must have two students solving the labs together.

To register for the labs and for information about how the WebReg System works go to: WebReg Info.
Note: Group 6 and Group 7 is reserved for U3 students only.

Once you have registered in Web-Reg, you will be assigned to a Team in Microsoft Teams which will be mainly used for submission of lab reports and/or source code for each lab assignment. The Team will consist of a main chat channel and a number of private sub-channels dedicated to each sub-group consisting of 2 students. The main chat will be used for communication between a lab assistant and the whole group - if necessary outside the scheduled lab sessions. The private channels should be used for lab submissions. For example Team_TDDC17-2023-Group 1 is a dedicated Team for Group 1. More information about working with Microsoft Teams can be found here.

Working on Lab Assignments

There are three ways you can work on your lab assignments:

  1. On site (i.e. at campus), during scheduled lab sessions. It is possible to work on the labs outside the scheduled sessions when a lab room is not booked for another course.
  2. Using your own computer and downloaded software (restrictions apply, see the comment below). Simply follow the instructions on the specific lab assignment's web-page to download the necessary code and software.
  3. Using your own computer and a remote desktop/login with 3 variations. Detailed information can be found here:
    1. RDP client: supports graphics and the connection is made directly to one of the physical computers available during scheduled lab sessions. This option should ensure best performance.
    2. Thinlinc client: also supports graphics, but the performance may be lower at times due to hardware limitations and depending on the number of active connections.
    3. SSH: limited to terminal/console mode. Most limited, but can be used when working on the Planning lab.
Note, most of the lab assignments can be done using your own computer and require only basic setup that includes downloading free software i.e. java and/or python and Eclipse/PyCharm IDE. The exception is part of the Planning lab (lab 6) which requires running specialised planners that are installed on the computers available at LiU. In this case one is required to remotely login to perform this part of the assignments or do them on a lab computer on site.

Deadlines

There is a semi-hard deadline of having the labs done before the exam. This is beneficial to you in two respects. Firstly, it will help you in passing the exam. Secondly, our ability to correct labs after the period ends decreases radically due to time constraints. For prompt registration of lab results it is best to get them in before the exam.

To make it easier for you to plan your participation in the lab course we have provided you with some guidelines below for when the labs should be completed. These are only guidelines! Remember that there are six labs and thirteen teacher aided lab occasions. This amounts to two lab occasions per lab with some slack. Remember to read the designated chapters in the book in advance to be as efficient as possible. We also encourage you to work outside of the teacher assisted lab hours if possible.

Lab Assignments

Six labs are planned for the course. Note, the main programming language for labs 1, 2, and 5 is Java, with exception of lab 1 which can alternatively be completed in Python.

Lab 1: Intelligent Agents (java/python) , recommended turn-in date: week 36

Lab 2: Search (java), recommended turn-in date: week 37

Lab 3: Deep Learning, recommended turn-in date: week 38

Lab 4: Bayesian Networks, recommended turn-in date: week 39

Lab 5: Reinforcement Learning (java), recommended turn-in date: week 40

Lab 6: Planning, recommended turn-in date: week 41
(New planning lab for TDDC17 in 2023 is ready!)

How to report your results

The requirements for reporting your results for each lab assignment are listed on the respective web pages. In some cases, a short demonstration to a lab assistant is required that will be done during scheduled lab sessions. After the demonstration has been accepted, submit the lab in a designated private sub-channel for your group in Microsoft Teams, i.e. using "file/upload" functionality.

Page responsible: Fredrik Heintz
Last updated: 2023-09-28