Undergraduate Course: Automated Planning (Level 10) (INFR10045)
Course Outline
| School | School of Informatics | 
College | College of Science and Engineering | 
 
| Course type | Standard | 
Availability | Available to all students | 
 
| Credit level (Normal year taken) | SCQF Level 10 (Year 4 Undergraduate) | 
Credits | 10 | 
 
| Home subject area | Informatics | 
Other subject area | None | 
   
| Course website | 
http://www.inf.ed.ac.uk/teaching/courses/plan | 
Taught in Gaelic? | No | 
 
| Course description | The aim of this course is to provide a solid grounding in artificial intelligence techniques for planning, with a comprehensive view of the wide spectrum of different problems and approaches, including their underlying theory and their applications. | 
 
 
Information for Visiting Students 
| Pre-requisites | None | 
 
| Displayed in Visiting Students Prospectus? | Yes | 
 
 
Course Delivery Information
| Not being delivered |   
Summary of Intended Learning Outcomes 
1 - Understand and formalize different planning problems.   
2 - Discuss the theoretical and practical applicability of different approaches.   
3 - Have the basic know how to design and implement planning systems.   
4 - Ability to review planning literature relevant to an area covered in the course.  
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Assessment Information 
Written Examination 70  
Assessed Assignments 30  
Oral Presentations 0  
 
 
Assessment 
- Practical exercise with automated planning systems 
- Survey of techniques used in nominated planning systems 
- Literature review of a selected area 
 
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year. |  
 
Special Arrangements 
| None |   
 
Additional Information 
| Academic description | 
Not entered | 
 
| Syllabus | 
Core Elements 
 
* Introduction and overview: intuitions and motivations. Basic conceptual model for planning: state transition systems, classical assumptions. Overview of different planning problems and approaches.  
* Classical planning: The classical planning problem. Situation Calculus and the Frame Problem. Classical representations and languages (e.g., STRIPS-like). Overview of State-Space Planning and Plan-Space Planning. 
* Hierarchical Task Network Planning. Partial-Order Planners. Mixed-initiative Planners.  
* Neoclassical Planning: Modern approaches to the classical planning problem: e.g., Planning-Graph techniques, SAT-based planning.  
* Heuristics and Control Strategies: Heuristics (in state-space and plan-space planning). Hand-coded control rules and control strategies. Deductive planning and control strategies in deductive planning.  
* Planning with Time and Resources: Basics of point and interval temporal algebra. Temporal constraints networks. Planning with temporal operators. Integrating planning and scheduling  
* More advanced planning topics: Knowledge Engineering for Planning (including advanced representations), distributed multi-agent planning, and plan execution.  
* Case Studies and Applications: A selection from robotics, manufacturing, assembly, emergency response, space exploration, games, planning for the web, etc. 
 
Areas Covered by Self-Study and Literature Review 
* Scheduling: Linear and Integer Programming. Dynamic Scheduling. Applications to real world scheduling problems. Design, development and implementation of scheduling systems.  
* Planning under uncertainty: different sources of uncertainty (e.g., nondeterministic actions, partial observability). Extensions to classical approaches (e.g., plan-space, planning-graph and propositional satisfiability techniques). Planning based on Markov Decision Processes. Planning based on Model Checking.  
 
Relevant QAA Computing Curriculum Sections:  Artificial Intelligence | 
 
| Transferable skills | 
Not entered | 
 
| Reading list | 
"Automated Planning: Theory and Practice" by M. Ghallab, D. Nau, and P. Traverso (Elsevier, ISBN 1-55860-856-7) 2004. | 
 
| Study Abroad | 
Not entered | 
 
| Study Pattern | 
Lectures	20 
Tutorials	0 
Timetabled Laboratories	0 
Non-timetabled assessed assignments	30 
Private Study/Other	50 
Total	100 | 
 
| Keywords | Not entered | 
 
 
Contacts 
| Course organiser | Dr Amos Storkey 
Tel: (0131 6)51 1208 
Email:  | 
Course secretary | Miss Kate Weston 
Tel: (0131 6)50 2692 
Email:  | 
   
 
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