Knowledge-Based Systems

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

Teachers

Person in charge

• Javier Vazquez Salceda ( )
• Ramon Sangüesa Sole ( )

Others

• Santiago Marco Sola ( )

Weekly hours

Competences

Transversal Competences

Transversals

• CT4 [Avaluable] - Teamwork. Be able to work as a member of an interdisciplinary team, either as a member or conducting management tasks, with the aim of contributing to develop projects with pragmatism and a sense of responsibility, taking commitments taking into account available resources.
• CT5 [Avaluable] - Solvent use of information resources. Manage the acquisition, structuring, analysis and visualization of data and information in the field of specialty and critically evaluate the results of such management.

Basic

• CB1 - That students have demonstrated to possess and understand knowledge in an area of ??study that starts from the base of general secondary education, and is usually found at a level that, although supported by advanced textbooks, also includes some aspects that imply Knowledge from the vanguard of their field of study.
• CB2 - That the students know how to apply their knowledge to their work or vocation in a professional way and possess the skills that are usually demonstrated through the elaboration and defense of arguments and problem solving within their area of ??study.
• CB4 - That the students can transmit information, ideas, problems and solutions to a specialized and non-specialized public.

Technical Competences

Especifics

• CE02 - To master the basic concepts of discrete mathematics, logic, algorithmic and computational complexity, and its application to the automatic processing of information through computer systems . To be able to apply all these for solving problems.
• CE15 - To acquire, formalize and represent human knowledge in a computable form for solving problems through a computer system in any field of application, particularly those related to aspects of computing, perception and performance in intelligent environments or environments.
• CE18 - To acquire and develop computational learning techniques and to design and implement applications and systems that use them, including those dedicated to the automatic extraction of information and knowledge from large volumes of data.

Generic Technical Competences

Generic

• CG2 - To use the fundamental knowledge and solid work methodologies acquired during the studies to adapt to the new technological scenarios of the future.
• CG4 - Reasoning, analyzing reality and designing algorithms and formulations that model it. To identify problems and construct valid algorithmic or mathematical solutions, eventually new, integrating the necessary multidisciplinary knowledge, evaluating different alternatives with a critical spirit, justifying the decisions taken, interpreting and synthesizing the results in the context of the application domain and establishing methodological generalizations based on specific applications.
• CG5 - Work in multidisciplinary teams and projects related to artificial intelligence and robotics, interacting fluently with engineers and professionals from other disciplines.

Objectives

1. To know and understand the concept of a knowledge-based system, its relationship with cognition and with the representation of knowledge
   Related competences: CG2, CG4, CT5, CB1, CB2, CB4, CE15,
2. To know and understand the different architectures of knowledge-based systems
   Related competences: CG2, CG4, CT5, CB2, CB4, CE15,
3. To know and understand the various forms of knowledge representation, reasoning and to practice their design and implementation implementation in the various architectures of knowledge-based systems
   Related competences: CG5, CT4, CE02, CE18,

Contents

1. Introduction to Knowledge-Based Systems Systems based on knowledge. Characteristics. components Problems solvable through SBCs.
   A thorough exploration of the different types of Knowledge-Based Systems, their components and applications.
2. Reasoning Based on Semantic/Procedural Knowledge
   Types of Knowledge. Knowledge representation schemes.
   Semantic Knowledge: Semantic Networks. Logical description. Networks of Frames. Ontologies. Ontological reasoning
   Procedural knowledge. Rule-based reasoning systems. Fact bases, knowledge bases, inference engine, meta-knowledge, ...
   Knowledge engineering. Phases of knowledge engineering. Knowledge management.
   SBCs with more than one Knowledge Representation Scheme. Meta-knowledge, combination of results.
3. Reasoning Based on Experience
   Reasoning Based on Experience
   Episodic knowledge: Reasoning based on experience. Modeling experience with Cases, Case-Based Reasoning (CBR). Fundamentals of CBR: Introduction, Cognitive theory, Basic cycle of reasoning. Academic Examples/Demonstrators.
   Components of a CBR system: Structure of the cases. Organization of the Library/Case Base. Recovery of cases. Adaptation of cases. Case evaluation. Case study.
   Application of a CBR system to a real case. Important aspects in the development of CBR systems.
   Reflexive Reasoning in CBR systems. Maintenance of a CBR system. Industrial applications of CBR systems. CBR system development tools
   Evaluation of CBR systems. Advanced topics in CBR: Temporal CBR, Spatial CBR, Hybrid CBR Systems
4. Collaborative Reasoning
   Collaborative Reasoning
   Introduction: Intelligent Decision Support Systems (IDSS), Recommender Systems. General architecture of a recommender system.
   Classification of Recommender Systems. Basic Recommendation techniques: Collaborative Filtering, Content-based Filtering.
   Other Recommendation techniques: knowledge-based (case-based, constraint-based), community-based, demographic-based, hybrid approaches
   KPIs in Recommendation Systems: performance, competence. Evaluation of the quality of a Recommendation System: quantitative measures, qualitative measures
   Applications of Recommendation Systems (Amazon, Netflix, ...). Future trends in Recommendation Systems

Activities

Activity Evaluation act

Teaching methodology

Evaluation methodology

Bibliography

Basic:

• Knowledge representation and reasoning [Recurs electrònic] - Brachman, Ronald J; Levesque, Hector J, Elsevier, 2004. ISBN: 9781558609327
  
• An Introduction to knowledge engineering - Kendal, S. L; Creen, M, Springer, [2007]. ISBN: 9781846284755
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991004152019706711&context=L&vid=34CSUC_UPC:VU1&lang=ca

Previous capacities