Paper Info
Title
Improving a Planner's Performance through Online Heuristic Configuration of Domain Models.
Abstract
The separation of planner logic from domain knowledge supports the use of reformulation and configuration techniques, such as macro-actions and entanglements, which transform the model representation in order to improve a planner’s performance. One drawback of such an approach is that it may require a potentially expensive training phase.In this paper, we introduce heuristic approaches for the online configuration of planning domain models. The proposedheuristics consider different aspects of PDDL-encoded operators for reordering such operators in the domain model, relying on the assumption that the way in which operators are encoded carries useful information about their expected use
Year
Venue
Field
2017
SOCS
Drawback,Heuristic,Domain knowledge,Model representation,Computer science,Planner,Theoretical computer science,Heuristics,Artificial intelligence,Operator (computer programming),Domain model
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Mauro Vallati121646.63
Lukás Chrpa29923.15
Thomas Leo McCluskey38413.00