Subject description - BE4M36PUI
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Explanatory Notes
Instructions
Web page:
https://cw.fel.cvut.cz/wiki/courses/pui/start
Anotation:
The course covers the problematic of automated planning in artificial intelligence and focuses especially on domain independent models of planning problems: planning as a search in the space of states (state-space planning), in the space of plans (plan-space planning), heuristic planning, planning in graph representation of planning problems (graph-plan) or hierarchical planning. The students will also learn about the problematic of planning under uncertainty and the planning model as a decision-making in MDP and POMDP.
Course outlines:
| 1. | | Introduction to the problematic of automated planning in artificial intelligence |
| 2. | | Representation in form of search in the space of states (state-space planning) |
| 3. | | Heuristic planning using relaxations |
| 4. | | Heuristic planning using abstractions |
| 5. | | Structural heuristics |
| 6. | | The Graphplan algorithm |
| 7. | | Compilation of planning problems |
| 8. | | Representation of the planning problem in form of search in the space of plans (plan-space planning) |
| 9. | | Hierarchical planning |
| 10. | | Planning under uncertainty |
| 11. | | Model of a planning problem as a Markov Decision Process (MDP) |
| 12. | | Model of a planning problem as a Partially Observable Markov Decision Process (POMDP) |
| 13. | | Introduction to planning in robotics |
| 14. | | Applications of automated planning |
Exercises outline:
| 1. | | Planning basics, representation, PDDL and planners |
| 2. | | State-space planning, Assignment 1 |
| 3. | | Relaxation heuristics, Assignment 1 Consultations |
| 4. | | Abstraction heuristics, Assignment 1 Deadline |
| 5. | | Landmark heuristics, Assignment 1 Results/0-point Deadline |
| 6. | | Linear Program formulation of heuristics |
| 7. | | Compilations |
| 8. | | Partial-order planning |
| 9. | | Hierarchical Planning |
| 10. | | Planning with uncertainty, Assignment 2 |
| 11. | | Planning for MDPs, Assignment 2 Consultations |
| 12. | | Planning for POMDPs, Assignment 2 Consultations |
| 13. | | Monte Carlo tree search, Assignment 2 Deadline |
| 14. | | Consultations of exam topics, Assignment 2 Results/0-point Deadline, Credit |
Literature:
* Malik Ghallab, Dana Nau, Paolo Traverso: Automated Planning: Theory & Practice, Elsevier, May 21, 2004
*
https://www.coursera.org/course/aiplan
Requirements:
Subject is included into these academic programs:
| Page updated 12.10.2024 17:51:12, semester: L/2023-4, Z,L/2024-5, Z/2025-6, Send comments about the content to the Administrators of the Academic Programs |
Proposal and Realization: I. Halaška (K336), J. Novák (K336) |