Artificial Intelligence (AI) is about creating algorithms to perform tasks in a way that we believe is intelligent. AI is about creating algorithms to make robots perform such tasks. Modern AI algorithms play games (e.g. chess), prove theorems (e.g. verification), discover patterns in data (e.g. explanations), analyze complex sequences (e.g. DNA), make ``life or death’’ decisions (e.g. matching organs to patients), optimize distributions (e.g. food, refugees, housings), drive cars (e.g. Tesla), play soccer, etc.
Learning Goals and Syllabus
The goal of the course is that students gain an understanding of some of the fundamental methods and algorithms of AI, and an appreciation of how they can be applied to interesting practical problems. This aligns with the objectives of the ERC AMPLify Project in which the goal is to develop models for allocation problems in practice, to design mechanisms for such applications and analyze them. For example, one such application is the stable marriage assignment problem with allocation objectives such as egalitarian welfare and utilitarian welfare.
You can download the syllabus for this course HERE . Please check for updates on lecture and project topics in the upcoming weeks!
This course has three components: lectures, tutorials and lab exercises.
The lectures will introduce selected basic topics such as search, game playing, decision making, planning, machine learning and probabilistic reasoning and resource allocation.
The tutorials will allow students to apply algorithms on simple 'toy' examples.
The lab exercises will provide to the students the opportunity to develop a small project in some area of AI: social choice, fair division, learning, planning, theorem proving, etc.
The general prerequisites of the TU Berlin Summer University are the following: at least one year of university experience + English level B2 or equivalent.
The AI course also requires:
1. Basic programming skills: C++ or Java or PHP or Prolog (advanced
programming skills are not necessary).
2. Basic LaTeX skills: a typesetting system.
3. Basic knowledge: algorithms, mathematics.
Dr. Martin Aleksandrov obtained a Bachelor degree in Computer Science from Sofia University, Bulgaria. He also received a Master degree in Computer Science from Technical University of Dresden, Germany. In addition, Martin obtained qualifications as Bachelor in Physics and Master in Probability Theory and Statistics from Sofia University, Bulgaria.
Martin received his PhD in Computer Science from UNSW Sydney, Australia. He was an intern at Fondazione Bruno-Kessler (FBK in Trento, Italy) and Australian ICT Research Centre of Excellence (fka NICTA in Sydney, Australia). He also worked at NOVALINCS (fka CENTRIA in Lisbon, Portugal).
He won the Computational Sustainability Outstanding Student Paper Award at 24th IJCAI 2015, Buenos Aires, Argentina, and Best Paper Award at 40th KI 2017, Dortmund, Germany.
Please direct questions about the course to the TU Berlin Summer University Team at: summeruniversity(at)tubs.de . We will answer your questions and direct specific queries regarding course content to the course lecturers where necessary.
Registration for Term 3 is now closed. Check out our program for Term 4 or Winter 2020 !