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View all- Morisset BGhallab M(2008)Learning how to combine sensory-motor functions into a robust behaviorArtificial Intelligence10.1016/j.artint.2007.07.003172:4-5(392-412)Online publication date: 1-Mar-2008
Learning How to Combine Sensory-Motor Modalities for a Robust Behavior
Pages 157 - 178
Abstract
We are proposing here an approach and a system, called robel, that enables a designer to specify and build a robot supervision system which learns from experience very robust ways of performing a task such as "navigate to". The designer specifies a collection of Hierarchical Tasks Networks (HTN) that are complex plans, called modalities, whose primitives are sensory-motor functions. Each modality is a possible combination these functions for achieving the task. The relationship between supervision states and the appropriate modality for pursuing a task is learned through experience as a Markov Decision Process (MDP) which provides a general policy for the task. This MDP is independent of the environment; it characterizes the robot abilities for the task.
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- Learning How to Combine Sensory-Motor Modalities for a Robust Behavior
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Learning how to combine sensory-motor functions into a robust behavior
This article describes a system, called Robel, for defining a robot controller that learns from experience very robust ways of performing a high-level task such as ''navigate to''. The designer specifies a collection of skills, represented as ...
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Published In
October 2001
289 pages
ISBN:3540001689
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 21 October 2001
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Cited By
View all- Morisset BGhallab M(2008)Learning how to combine sensory-motor functions into a robust behaviorArtificial Intelligence10.1016/j.artint.2007.07.003172:4-5(392-412)Online publication date: 1-Mar-2008