Checking date: 27/04/2023

Course: 2023/2024

Automatic Planning
Master in Computer Science and Technology (Plan: 462 - Estudio: 71)

Coordinating teacher: GARCIA OLAYA, ANGEL

Department assigned to the subject: Computer Science and Engineering Department

Type: Compulsory
ECTS Credits: 3.0 ECTS


Requirements (Subjects that are assumed to be known)
- 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
Skills and learning outcomes
Description of contents: programme
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
Learning activities and methodology
Lectures Weekly homework Final project with oral presentation Individual office hours
Assessment System
  • % end-of-term-examination 50
  • % of continuous assessment (assigments, laboratory, practicals...) 50
Calendar of Continuous assessment
Basic Bibliography
  • James F. Allen, James Hendler y Austin Tate (eds.). Readings in planning. Morgan Kaufmann, 1990..
  • Malik Ghallab, Dana Nau, Paolo Traverso. Automated Task Planning. Theory & Practice. Morgan Kaufmann, 2004.
  • Stuart Russell y Peter Norvig. Artificial Intelligence: A modern approach. Prentice Hall. 2010
Recursos electrónicosElectronic Resources *
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The course syllabus may change due academic events or other reasons.