Richardson, Nona Elizabeth (2006) Towards inducing hierarchical task network domain models for AI planning from examples. In: Proceedings of Computing and Engineering Annual Researchers' Conference 2006: CEARC’06. University of Huddersfield, Huddersfield, pp. 1-5.
- Published Version
Domain modelling for AI Planning aims to form a database of facts about the ‘world’ being modelled.
This can be a complex process especially if there is a large number of objects or actions or both to be
modelled. This task can be facilitated by tools which induce operators or methods from examples.
Further, large and complex domains are more easily constructed if domain languages are used which
allow for hierarchical decomposition of domain components. Examples of such a decomposition are
class hierarchies and method hierarchies. This paper describes ongoing work which aims to
produce algorithms which learn effective hierarchical decompositions from examples.
|Item Type:||Book Chapter|
|Uncontrolled Keywords:||domain model, operators, methods, GIPO|
|Subjects:||T Technology > T Technology (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
|Schools:||School of Computing and Engineering
School of Computing and Engineering > Computing and Engineering Annual Researchers' Conference (CEARC)
|Depositing User:||Graham Stone|
|Date Deposited:||03 Apr 2009 10:44|
|Last Modified:||02 Dec 2016 05:30|
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