Course syllabus

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DAT615 DAT615 Neuro-symbolic AI lp2 HT26 (7.5 hp)

Course is offered by the department of Computer Science And Engineering

Contact details

For questions about their lectures, contact the respective lecturer. For questions about assignments, contact the TA. Note that email is the preferred mode of contact, not Canvas DMs. The teachers will monitor their emails much more regularly than Canvas DMs.  

Student Representatives

TBA

Course purpose

The purpose of the course is to introduce the students to the field of neuro-symbolic AI. Recent advances in neural networks have quickly moved the state of the art forward for many applications, not least natural language processing and computer vision. But neural models still have weaknesses, for instance when it comes to reliably reasoning logically or planning. This is were methods from symbolic AI (e.g. rule based and heuristic methods) still dominate. The aim of neuro-symbolic AI is to combine the two approaches to get the best from both worlds. It will also allow us to tackle problems which neither method on its own is particularly good at. In this course, we will focus on two application areas: cognitive modeling and languages for emergent communication (with Dubhashi), and program synthesis and mathematics (with Johansson). Towards the end of the course, students should have sufficient knowledge to be able to follow recent research papers in these areas. The final two weeks are dedicated to presentation and discussion of such state of the art research articles. 

Schedule

Please refer to TimeEdit for details of the schedule. Note that rooms might vary between lectures (for reasons beyond our control). 

An overview of the lecture topics will be posted at the start of the course.

Office Hours with TAs: Getting help with Assignments

If you want to get help with the assignments you may come to the Office Hours and speak to the TA. The date and time will be announced when the course starts. Note that you will need to sign up for a slot in advance: if no one plan to attend, we will cancel the session.

Course literature

The course literature consist of recent articles from the research literature. Links to reading material related to each lecture will be linked to from the respective lecture page, clearly stating which are obligatory readings and which are supplementary for the interested. After the lecture, you will also find copies of the slides there. You should be prepared to read quite a lot each week for this course, including scientific articles. 

Course design

The course has two lectures per week. The lectures will introduce topics from both symbolic AI, machine learning and neuro-symbolic AI. Students are expected to attend lectures and to read the material linked from each lecture page. To contact the teachers, please use email. There will likely be a delay in getting a reply to messages sent in Canvas.

More information about the assignments will follow.

Changes made since the last occasion

The following changes have been made since the last occasion (HT25):

  • The lectures have been updated to reflect new research in the field of neuro-symbolic AI.

Learning objectives and syllabus

Learning objectives:

After completion of the course the student should be able to:

  • Separate what characterise symbolic and neural AI.
  • Explain what neuro-symbolic AI encompasses.
  • Apply and implement methods and algorithms for neural AI
  • Apply and implement methods algorithms for symbolic AI.
  • Apply and implement neuro-symbolic AI methods and algorithms.
  • Read and understand recent research articles in neuro-symbolic AI.

 

Link to the syllabus on Studieportalen.

https://www.chalmers.se/en/education/your-studies/find-course-and-programme-syllabi/course-syllabus/DAT615/?acYear=2026/2027

 

Examination form

The course will have a hall exam in January and potential re-exams in the spring and in August (note that due to the very low number of students taking the re-exams, we strongly encourage notification also to the examiner stating which re-exam you intend to take, there has been cases where few or no students register in which case time is better spent elsewhere than in constructing exam questions).

No aids are allowed. The exam is compulsory. The exam has two parts. The first part is 20 short multiple choice questions on the full range of topics covered in the course. You may be asked to choose one or more alternatives, plus provide a one sentence justification. The second part contains two longer-answer questions of a problem solving nature, but will not require programming, complicated calculations or anything like that which requires additional tools.  

More information about the assignments will follow here.

Course summary:

Course Summary
Date Details Due