Reasoning and decision-making are basic functionalities that are expected from any intelligent system. One branch of artificial intelligence (AI) is commonly referred to as Knowledge Representation and Reasoning (KRR). Within this field, methods for solving difficult search problems have been developed. One such approach is called Answer Set Programming (ASP) and has been identified as a significant contribution to the research field of AI. ASP has been successfully applied for solving problems in domains such as bioinformatics, scheduling, timetabling, dynamic reconfiguration, and software engineering.
Semantic-based technology (or only semantic technology) is another KRR consolidated technology that aims to give meaning to the disparate and raw data that surrounds us. The main standards that Semantic Technology builds on are the RDF (Resource Description Framework), SPARQL (SPARQL Protocol and RDF Query Language), and, optionally, OWL (Web Ontology Language).
During this course, we will show how to use ASP and semantic technology for the fast prototyping of intelligent systems that need to deal with autonomous decision-making processes.
The course is for professionals in industry and public organisations who have knowledge in engineering and system development, who want to gain deepened knowledge in AI.
There are three main expected learning outcomes for the students attending this course:
- Know basic principles of Answer Set Programming and semantic technology to be able to describe and apply symbolic reasoning methods.
- Use both answer sets and semantic web solvers for modeling and implementing of intelligent systems.
- Be able to judge the suitability of symbolic reasoning methods for a given problem.
The course corresponds to 3 ECTs and consists of eight lectures with exercises, divided over three days, combined with home assignments. The course is developed by the Department of Computing Science as part of AI Competence for Sweden, in collaboration with Örebro University and their SMARTER program for industry. A certificate of attendance will be provided, but no formal credits in this edition of the course. Note that presence during the three days and submitting home assignments is obligatory to receive the certificate.
Time: 9.00-15.00
Dates 2021: (first edition: January 22, February 5, February 12 ; and February 26 (presentations of homework))
Second edition: November 19, November 26, December 3, and December 10 (presentations of homework)
Location: Zoom or Seminar room at the MIT-Place, MIT building.
Register using this link before November 17.
The lectures will be held in the Seminar room, MIT-Place, MIT building, a limited number can participate in person, others can participate through Zoom.
For more information, please, contact Juan Carlos Nieves: juan.carlos.nieves@umu.se
The course is part of a package of introductory courses for industry and public organisations developed by Umeå University for increasing knowledge in the field of artificial intelligence. For an overview, please, visit this page.