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Planning Graph Based Reachability Heuristics Tutorial
Planning Graph Based Reachability Heuristics
Tutorial presented at
ICAPS 2006
Presenter Biographies: [txt]
Tutorial Description
The primary revolution in automated planning in the last decade has
been the very impressive scale-up in planner performance. A large part
of the credit for this can be attributed squarely to the invention and
deployment of powerful reachability heuristics. Most, if not all,
modern reachability heuristics are based on a remarkably extensible
datastructure called the planning graph--which made its debut as a bit
player in the success of Graphplan, but quickly grew in prominence to
occupy the center-stage.
In this tutorial, we will start with a discussion of the foundations
of reachability analysis with planning graphs. We will then discuss
the many ways of applying this analysis to develop scalable planners.
Starting with classical planning, we will discuss heuristics for
cost-based planning, over-subscription planning, planning with
resources, temporal planning, non-deterministic planning as well as
stochastic planning.
The intended audience is new researchers in planning or experienced
researchers from another specialization. The audience should have
some familiarity with classical planning models, and preferably also
temporal and non-deterministic plannning.
Outline: [txt]
ICAPS 06 Materials
Slides:
[ppt][pdf]
Audio:[mp3 #1 (Rao)]
[mp3 #2 (Dan) ]
[mp3 #3 (Rao) ]
IJCAI-07 Materials
Syllabus: [txt]
Slides:
[ppt]
Audio:[wav #1]
[wav #2]
Technical Report
We also have a survey article on planning
graph heuristics that contains most of the material covered in the
tutorial.
How to skin a planning graph for fun and profit: A Tutorial on Planning Graph Based
Reachability Heuristics.
Daniel Bryce and Subbarao Kambhampati.
ASU CSE TR-06-007,AI Magazine Vol 27, No. 4, Winter 2006
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