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Towards High-performance Robot Plans with Grounded Action Models: Integrating Learning Mechanisms into Robot Control Languages (bibtex)
@INPROCEEDINGS{kirsch_towards_2005,
  author = {Kirsch, Alexandra},
  title = {Towards High-performance Robot Plans with Grounded Action Models:
	Integrating Learning Mechanisms into Robot Control Languages},
  booktitle = {{ICAPS} Doctoral Consortium},
  year = {2005},
  abstract = {For planning in the domain of autonomous robots, abstraction of state
	and actions is indispensable. This abstraction however comes at the
	cost of suboptimal execution, as relevant information is ignored.
	A solution is to maintain abstractions for planning, but to fill
	in precise information on the level of execution. To do so, the control
	program needs models of its own behavior, which could be learned
	by the robot automatically. In my dissertation I develop a robot
	control and plan language, which provides mechanisms for the representation
	of state variables, goals and actions, and integrates learning into
	the language.}
}
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Last edited 29.01.2013 17:37 by Quirin Lohr