None

- To present state-of-the-art automated planning techniques - To characterize every technique as well as the domains they suit better - To use tools that implement techniques discussed in class - To identify different open issues for research in order to suggest new Master and PhD thesis

1. Introduction 1.1 Knowledge representation 1.2 Heuristic Search 2. Classical planning 2.1 State space. STRIPS 2.2 Partial plans. UCPOP 3. Planning based on plan graphs 3.1 Plan graphs. GRAPHPLAN 3.2 SAT planning. SATPLAN 4. Heuristic planning 4.1 Early approaches. HSP, FF 4.2 New heuristics and planners. Fast downward, pattern data bases, landmarks, symbolic planning, portfolios 4.3 Hierarchical Task Networks (HTN). SHOP2 5. Machine learning in planning 6. Other planning paradigms 6.1 Temporal planning (scheduling) 6.2 Partial Satisfaction Planning 6.3 Planning under uncertainty 6.4 Timeline-based planning

AF1 Theoretical Class. AF2 Practical Classes. AF5 Tutorials. AF6 Group Work. AF7 Individual Student Work. AF8 Midterm and Final Exams. MD1 Instructor's classroom presentations with IT and audiovisual support, developing the main concepts of the subject and providing bibliography to complement student learning. MD2 Critical reading of texts recommended by the course instructor. MD3 Resolution of practical cases, problems, etc., posed by the instructor individually or in groups. MD4 In-class presentation and discussion, moderated by the instructor, on topics related to the course content, as well as practical cases. MD5 Preparation of individual or group assignments and reports.