Declarative Modeling - Single View

The goal of this course is to learn and experience advanced modeling and implementation techniques in the area of declarative problem solving, more precicely, answer set programming (ASP); it is conceived as a continuation of the course on Declarative Problem Solving and Optimization.

• 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

• Motivation
• Sophisticated modeling
• Multi-shot solving
• Theory solving
• Heuristic-driven solving
• Systems
• Preferences and Optimization
• Applications

MSc students who want to deepen their practical knowledge in declarative problem solving, more precisely, answer set programming (ASP)