Introduction to the planning techniques as problem solving tools. The main approaches to automatic planning will be presented. The student must be able to implement a planner and solve a case study.
The second part is devoted to introduce the main concepts on approximate reasoning, focused on Fuzzy Logic. The use of fuzzy logic in rule-based systems will be presented. The student must be able to apply this methodology to a particular problem. Web: moodle URV Mail:
Teachers
Person in charge
Aida Valls (
)
Weekly hours
Theory
2
Problems
0
Laboratory
1
Guided learning
0
Autonomous learning
0
Competences
Generic Technical Competences
Generic
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
CEA2 - Capability to understand the basic operation principles of Planning and Approximate Reasoning main techniques, and to know how to use in the environment of an intelligent system or service.
Professional
CEP1 - Capability to solve the analysis of information needs from different organizations, identifying the uncertainty and variability sources.
CEP8 - Capability to respect the surrounding environment and design and develop sustainable intelligent systems.
Transversal Competences
Teamwork
CT3 - Ability to work as a member of an interdisciplinary team, as a normal member or performing direction tasks, in order to develop projects with pragmatism and sense of responsibility, making commitments taking into account the available resources.
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
Know the fundamental basis of Artificial Intelligence
Related competences:
CG3,
Support the implementation with the use of programming languages user manuals.
Related competences:
CEP1,
Identify the possibilities and limitations of Artificial Intelligence
Related competences:
CT6,
CEA2,
CEP8,
Apply the model of search space to decompose a problem.
Related competences:
CT3,
CEA2,
Be able to discuss the results obtained on the basis of the theoretical models studied.
Related competences:
CEA2,
CEP1,
Formalize a problem in terms of fuzzy logic and apply reasoning methods on this uncertainty model.
Related competences:
CEA2,
CEP1,
Contents
Approximate reasoning
1.1 Probabilistic models
1.2 Fuzzy Logic and Fuzzy expert systems
1.3 Models based on the Theory of Evidence
Planning techniques
Activities
Lectures and lab practise about Approximate Reasoning
Weakly, 2 hours theoretical lecture and1 h practise in laboratories.
Theory
14
Problems
0
Laboratory
7
Guided learning
0
Autonomous learning
21
Lectures and exercises about Planning.
Weakly, 2 hours theoretical lecture and1 h practise in laboratories.
Theory
14
Problems
0
Laboratory
8
Guided learning
0
Autonomous learning
21
Teaching methodology
Oral exposition fo the teacher
Practical exercises with software tools.