Checking date: 24/05/2023

Course: 2023/2024

Search and Optimization
Master in Applied Artificial Intelligence (Plan: 475 - Estudio: 378)

Coordinating teacher: LINARES LOPEZ, CARLOS

Department assigned to the subject: Computer Science and Engineering Department

Type: Electives
ECTS Credits: 3.0 ECTS


Requirements (Subjects that are assumed to be known)
Programming Artificial Intelligence
The subject is devoted to the study of the main programming techniques and the design of algorithms (both deterministic and stochastic) for solving discrete optimization tasks, both constructive and traversing the solutions space.
Skills and learning outcomes
Description of contents: programme
1. Dynamic Programming 2. SAT Compilation 3. Search 3.1. Uninformed search 3.2. Heuristics: constraint relaxation and pattern databases 3.3. Heuristic search 4. Monte-Carlo Tree Search: 4.1. MCTS 4.2. UCT 4.3. MC- y DP-backups
Learning activities and methodology
Learning activities: Theoretical lectures (AF1) Practical sessions (AF4) Tutorials (AF5) Team work (AF6) Individual student work (AF7) Teaching methodologies: Resolution of practical cases, problems, etc... raised by the lecturer individually or in a group (MD3) Preparation of work and reports individually or in groups (MD5)
Assessment System
  • % end-of-term-examination 100
  • % of continuous assessment (assigments, laboratory, practicals...) 0

Calendar of Continuous assessment

The course syllabus may change due academic events or other reasons.