Logics for Artificial Intelligence

• Weekly hours
• Competences
• Objectives
• Contents
• Activities
• Teaching methodology
• Evaluation methodology
• Bibliography
• Web links
• Previous capacities

Teachers

Person in charge

• Antonio Moreno Ribas ( )

Weekly hours

Competences

Generic Technical Competences

Generic

• CG1 - Capability to plan, design and implement products, processes, services and facilities in all areas of Artificial Intelligence.
• CG3 - Capacity for modeling, calculation, simulation, development and implementation in technology and company engineering centers, particularly in research, development and innovation in all areas related to Artificial Intelligence.

Technical Competences of each Specialization

Academic

• CEA13 - Capability to understand advanced techniques of Modeling , Reasoning and Problem Solving, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.

Professional

• CEP3 - Capacity for applying Artificial Intelligence techniques in technological and industrial environments to improve quality and productivity.
• CEP5 - Capability to design new tools and new techniques of Artificial Intelligence in professional practice.

Transversal Competences

Information literacy

• CT4 - Capacity for managing the acquisition, the structuring, analysis and visualization of data and information in the field of specialisation, and for critically assessing the results of this management.

Reasoning

• CT6 - Capability to evaluate and analyze on a reasoned and critical way about situations, projects, proposals, reports and scientific-technical surveys. Capability to argue the reasons that explain or justify such situations, proposals, etc..

Objectives

1. Understand the basic tools of Mathematical Logic and their use as a knowledge representacion and reasoning mechanism within an intelligent system.
   Related competences: CT4, CEA13, CG3,
2. Know how to apply the tools of Mathematical Logic to solve specific problems.
   Related competences: CT6, CEA13, CEP3, CEP5, CG1,

Contents

1. First-Order Logic
   Use of first-order logic as a mechanism for knowledge representation and reasoning.
   Formalisation. Resolution. Model Theory.
2. Logic Programming
   Logic programming: facts and rules. Backwards reasoning. Cut operator. Negation as failure.
3. Description logics.
   Description logics. Language: concepts, rols and constants. Operators to define complex concepts. Reasoning mechanisms.
4. Inheritance networks.
   Defeasible reasoning on inheritance networks. Positive and negative links and paths. Admissible links and paths. Credulous extensions. Types of reasoning.
5. Default reasoning.
   Closed world reasoning. Circumscription. Default logic. Autoepistemic logic.
6. Knowledge graphs.
   Definition of Knowledge Graphs. Representation in RDF, RDF(S). Examples: DBpedia, wikidata. Ontologies. Queries in SPARQL.

Activities

Activity Evaluation act

Teaching methodology

Evaluation methodology

Bibliography

Basic:

• Knowledge representation and reasoning - Brachman, R.J.; Levesque, H.J, Elsevier, 2004. ISBN: 1558609326
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991002742679706711&context=L&vid=34CSUC_UPC:VU1&lang=ca

Complementary:

• Introductory logic and sets for computer scientists - Nissanke, N, Addison Wesley Longman , 1999. ISBN: 0201179571
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991002047609706711&context=L&vid=34CSUC_UPC:VU1&lang=ca

Web links

• Moodle space at URV https://campusvirtual.urv.cat

Previous capacities