Declarative Problem Solving and Optimization - Einzelansicht

We start on Friday 20th of October at 12:00. More information about the course can be found at Moodle. - cu

Answer Set Programming (ASP) is a prime approach to declarative problem solving. Although initially tailored to modeling problems in the area of Knowledge Representation and Reasoning (KRR), its attractive combination of a rich yet simple modeling language with high-performance solving capacities has sparked interests in academia and industry way beyond KRR. This course presents a detailed introduction to ASP, aiming at using ASP languages and systems for solving application problems. Starting from the essential formal foundations, it introduces ASP's solving technology, modeling language and methodology, while illustrating the overall solving process by practical examples.

• Answer Set Solving in Practice by Martin Gebser, Roland Kaminski, Benjamin Kaufmann, and Torsten Schaub. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan and Claypool
• Potassco User Guide by the Potassco team, https://github.com/potassco/guide/releases
• Answer Set Programming by Vladimir Lifschitz. Springer
• Knowledge Representation, Reasoning, and the Design of Intelligent Agents: The Answer-Set Programming Approach by Michael Gelfond and Yulia Kahl. Cambridge University Press

Offline communication is conducted primarily via the associated moodle page.

Announcements are also made through the email list of registered students in puls.

Questions can be addressed to asp@lists.cs.uni-potsdam.de​

A tutorial introduction to answer set programming, used in the projects, is given separately.

Motivation.

Marked exam and assignments

• Motivation
• Introduction
• Modeling
• Language
• Grounding
• Foundations
• Solving
• Advanced modeling

This is an introductory lecture for MSc students with varying backgrounds.