Allmänt
The course offers a broad introduction to main areas of Artificial Intelligence of importance to CS and IT , including
- search and problem-solving
- constraint solving, deduction, logic, and automated reasoning
- probabilistic inference and reasoning about uncertainty
- semantic technologies
- sequential decision-making, decision-making under uncertainty
- game-theoretic and adversarial decision-making
- adaptation and learning, especially reinforcement learning
The course will give an introduction to the main forms of advanced software tools for solving hard combinatorial problems that are increasing in importance both in A.I. and construction of intelligent systems as well as in the advanced automation in CS
and IT more generally. The question answered by the course is: what kind of advanced technologies are needed to get beyond current SW technologies, in important applications in IT and other industries?
Prerequisites of the course are: basic math, programming skills at the level of a 2nd/3rd year CS student, knowledge of basic data structures and algorithms.
Registration deadline has passed.
The course is lectured by Prof. Jussi Rintanen.
Schedule:
- Introduction, motivation (January 9) (intro, organization; Also read Reading Material below)
- Search, state-space search (January 16) pdf
- Search, model-based problem solving (January 23) pdf
- Logic: Propositional logic, solution methods, constraint solving (January 30) pdf
- Logic: Predicate logic, knowledge representation and semantic technologies, NLP semantics (February 6) pdf
- Reasoning under uncertainty (February 13) pdf
- Decision-making under uncertainty, MDPs (February 27) pdf
- Partial observability, reinforcement learning (March 5) pdf
- Multi-agent decision-making, game-tree search (March 12) pdf
- A.I. applications, future, summary (March 19) pdf
- The weekly lecture takes place in Otakaari 1 lecture hall A on Thursday from 12:15 until about 14:00. Course material corresponding to the lecture will (generally) be made available on Thursday right before the lecture (exceptionally a bit later, like Thursday evening or Friday morning). (LECTURES CANCELLED DUE TO VIRUS SCARE!)
- After the lecture, the course participants will read/view the lecture material and other material from the MyCourses page.
- New weekly exercise assignments will be available on Thursday (typically noon at the same time with the lecture materials, in some cases early evening.)
- For support and help with the exercises there are exercise sessions at the lecture halls T1 or T2 on Tuesday afternoon from 14:15 until 16:00 and from 16:15 until 18:00. You can also consult the teaching assistants through Slack. (EXERCISE SESSIONS CANCELLED DUE TO VIRUS SCARE!)
- There will be 2 weeks to complete the exercises: deadline is two weeks later on Wednesday at 23:59. Exercise assignments returned late (after the deadline) will still be accepted, but the points obtained are divided by 2 (so you get only 50 percent of the points.)
- Answers to exercise questions will be submitted through the MyCourses exercise pages. The multiple choice questions and the questions with textual or numeric answers will be graded immediately. Programming exercises (typically implemented with Python3) will be submitted through the same pages, but automated grading is through a batch processing service that may take up to 15 minutes to complete.
- The multiple choice questions can be only answered a limited number of times (twice!), so submit the answers only when you are absolutely sure you have them right. The other assignments, including the programming assignments, may be submitted any number of times.
To register for the Slack workspace for the course go to (link valid until March 20): https://join.slack.com/t/ai-course-hq/shared_invite/enQtOTU5MDMyMDc1OTIyLTViZWJiOGYwODA5MTcwN2E3YTQyNDE3NWQ5ZTQ2NWRkNTE4NTg4NjEyYzQ1NGUwYzA1NDcwZDlkY2QxMjIzNTg