|Dr Manfred Kerber Dr Mateja Jamnik||
10 credit module Semester 2
ObjectivesOn completion of this course, the student should:
Basic knowledge of AI Techniques and Logic. Some programming knowledge in Pop11 is helpful in order to benefit from the implementation examples, but not necessary.
The course has two components. In the first, the basic knowledge about planning is presented in a mixture of conventional lectures and exercise classes (together 2 hours per week throughout that part of the course). In the second, each student gives a presentation of a recent research paper.
The course will be assessed to 80% by a 2-hour unseen examination in May (on the material of the first component) and to 20% on the basis of the preparation and the presentation of a seminar. Presence of all participants is obligatory for this part of the course.
Recommended Books: Sections on planning in
|Artificial Intelligence - A Modern Approach||Stuart Russell & Peter Norvig||Prentice Hall 1995||Further Reading|
|Artificial Intelligence, 2nd Edition||Elaine Rich & Kevin Knight||McGraw-Hill 1994||Further Reading|
|Artificial Intelligence, Third edition||Patrick Henry Winston||Addison-Wesley 1992||Further Reading|
The following courses are currently planned, modifications are possible: (Slides and Exercises are available in gzipped PostScript files, during the course, spare copies can be found in the School's library, these should be taken first in order not to waste printer resources. The files will be made readable after the corresponding lectures.)
|1||Manfred||Basic notions of planning (Goals, Blocks world, Deductive Planning) Frame Problem, frame axioms (tractability), planning as search (breadth-first search, depth-first search, heuristic search)||l1.ps.gz l1.pdf||e1.ps.gz e1.pdf|
|2||Manfred||Planning with STRIPS, Representation, Search, Limits (interaction of partial goals, unsolvable problems), Planning for simultaneous goals (Solution to the so-called Sussman anomaly)||l2.ps.gz l2.pdf||e2.ps.gz e2.pdf|
|3||Manfred||Non-Linear Planning (basic idea and notions, classification and solution of conflicts, critics), Linear vs. non-linear planning||l3.ps.gz l3.pdf||e3.ps.gz e3.pdf|
|4||Manfred||Hierarchical Planning (Planning with abstraction of situations, Planning with abstraction of operators)||l4.ps.gz l4.pdf||e4.ps.gz e4.pdf|
|5||Mateja||Increasing the Flexibility in Planning||l5.ps.gz l5.pdf||e5.ps.gz e5.pdf|
|6||Mateja||Conditional Planning (sensing, dependence on unknown facts)||l6.ps.gz l6.pdf||e6.ps.gz e6.pdf|
|7||Mateja||Reactivity vs Deliberation||l7.ps.gz l7.pdf||e7.ps.gz e7.pdf|
|8||Mateja||Distributed Planning||l8.ps.gz l8.pdf||e8.ps.gz e8.pdf|
|9||Mateja||Multi-agent planning||l9.ps.gz l9.pdf||e9.ps.gz e9.pdf|
|General Search (without loopcheck)||search.p|
|General Search (with loopcheck)||search-w-loopcheck.p|
|Problem description of the kitchen problem||kitchen.p|
|Otter Example (without frame axioms)||otter1.in
|Otter Example (with frame axioms)||otter2.in
In the second part of the course, participants of the course will give
presentations of research papers from the following list, available as
A schedule for the student talks will be made available as ascii, dvi, Postscript, and pdf.
The criteria for assessing the presentations can be found as ascii, dvi, Postscript, and pdf files.
For the two extra lectures necessary to fit in all presentations we've booked on 5th May 11:00-12:00 and on 12th May 11:00-13:00 room Hills 216.
Maintained by M.Kerber@cs.bham.ac.uk
School of Computer Science
The University of Birmingham
Last update 24 May 2000