Kursuse eesmärk on anda üliõpilastele põhjalik arusaam intelligentsetes süsteemides kasutatavatest põhialgoritmidest ja metoodikatest, sealjuures varustada üliõpilasi oskustega valida ja rakendada nende süsteemide jaoks sobivaid algoritme.

The aim of the course is to provide students with a thorough understanding of the fundamental algorithms and methodologies used in intelligent systems, thereby equipping students with the skills to select and apply appropriate algorithms for these systems.

Õppeaine läbinud üliõpilane:
- kasutab keerukate probleemide esitamiseks sobivaid olekuruumi mudeleid;
- kirjeldab otsingualgoritmide erinevusi;
- rakendab vastavalt ülesandele sobivat otsingualgoritmi;
- kirjeldab planeerimisalgoritmide erinevusi;
- rakendab vastavalt ülesandele sobivat planeerimisalgoritmi;
- kirjeldab intelligentsete agentide arhitektuuride erinevusi;
- rakendab ülesannete lahendamiseks sobiva arhitektuuriga intelligentsete agentide algoritme;
- selgitab intelligentsete süsteemide eetilisi aspekte.

After completing this course, the student:
- uses appropriate state space models to represent complex problems;
- describes the differences between search algorithms;
- implements suitable search algorithms according to the task;
- describes the differences between planning algorithms;
- implements suitable planning algorithms according to the task;
- describes the differences between intelligent agent architectures;
- implements intelligent agent algorithms with appropriate architectures to solve tasks;
- explains the ethical aspects of intelligent systems.

Aines käsitletakse otsingu- ja planeerimisalgoritme ning intelligentsete agentide algoritme, mis on kasutusel robootikas ja muudes autonoomsetes süsteemides. Teemade hulgas on erinevad otsingualgoritmid, planeerimisalgoritmid erinevate stsenaariumite jaoks ning algoritmid nii individuaalsetele kui multiagentsüsteemidele. Aines osaleja saab lisaks teoreetilistele alustele ka praktilise kogemuse erinevate algoritmide realiseerimisest ja rakendamisest erinevates kontekstides.

This course explores a range of search and planning algorithms, along with intelligent agent methodologies, applicable to robotics and autonomous systems. Topics include various search strategies, planning techniques for different scenarios, and algorithms for individual and multi-agent systems. Participants will acquire both theoretical knowledge and practical experience in the development and application of these algorithms, adaptable to a wide range of contexts and systems.

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Russell, S.J and Norvig, P. Artificial intelligence: a modern approach, fourth editions, Pearson 2020

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