Symbolic Systems 1 (UvA, MSc AI, June 2020)

Contents:

1. Topics
2. Examples
3. Homework assignments

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Topics

Here is a short overview of the different topics that we will cover in the course, together with pointers to reading material.

(A) Problem solving & search

Subtopics:

• Problem solving and search in rational agents
• Propositional logic and SAT solving
• Constraint programming
• Integer linear programming

Reading material:

• Sections 3.1–3.4 of [Russell, Norvig, 2016].
• Sections 6.1–6.3 of [Russell, Norvig, 2016].
• Sections 7.1–7.6.1 of [Russell, Norvig, 2016].
• Appendix A.1 of [Russell, Norvig, 2016].
• Sections 2.0–2.2.2 of [Van Harmelen, Lifschitz, Porter, 2008].

(B) Non-monotonic reasoning and answer set programming

Subtopics:

• Non-monotonic reasoning
• Default logic
• Answer set programming (ASP)
• Problem solving using ASP

Reading material:

• Sections 6.0–6.2 of [Van Harmelen, Lifschitz, Porter, 2008].
• Sections 7.1–7.3.1 and 7.3.4–7.4 of [Van Harmelen, Lifschitz, Porter, 2008].
• Sections 2.0–2.3 of [Gebser, Kaminski, Kaufmann, Schaub, 2012].
• Chapter 3 of [Gebser, Kaminski, Kaufmann, Schaub, 2012].

(C) Automated planning

Subtopics:

• Classical planning
• Planning using problem solving (in particular: ASP)
• Extensions of classical planning

Reading material:

• Sections 10.0–10.2 and 10.4 of [Russell, Norvig, 2016].
• Section 11.3 of [Russell, Norvig, 2016].
• Chapter 8 of [Gebser, Kaminski, Kaufmann, Schaub, 2012]—for the homework assignment.

(D) Description logics and OWL

Subtopics:

• Description logics
• Web Ontology Language (OWL)
• Modelling and reasoning with ontologies

Reading material:

• Sections 8.0–8.2 of [Russell, Norvig, 2016].
• Sections 12.1–12.2 of [Russell, Norvig, 2016].
• Sections 3.0–3.2 and 3.7 of [Van Harmelen, Lifschitz, Porter, 2008].

References:

• [Russell, Norvig, 2016]: Stuart Russell, and Peter Norvig. Artificial Intelligence: A Modern Approach (3rd Ed.), Prentice Hall, 2016.
• [Van Harmelen, Lifschitz, Porter, 2008]: Frank van Harmelen, Vladimir Lifschitz, and Bruce Porter (Eds.). Handbook of Knowledge Representation, Elsevier, 2008.
• [Gebser, Kaminski, Kaufmann, Schaub, 2012]: Martin Gebser, Roland Kaminski, Benjamin Kaufmann, and Torsten Schaub. Answer Set Solving in Practice, Morgan & Claypool, 2012.

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Examples

Here are some Python notebooks that illustrate how to use various of the techniques that we cover in the course.

• How to call solvers for different search problems from Python:
  • SAT solving in Python
  • ASP solving in Python
  • CSP solving in Python
  • ILP solving in Python
• A very short guide to integer linear programming
• A short guide to answer set programming (using clingo and Python)
• How to solve 3-Coloring using SAT solving
• How to solve 3-Coloring using CSP solving
• How to solve 3-Coloring using ILP solving
• How to solve 3-Coloring using answer set programming
• How to solve Dominating Set using answer set programming

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Homework assignments

• Assignment 1 (programming)
• Assignment 2
• Assignment 3 (programming)

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