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The Spatial Semantic Hierarchy (2000)
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| Venue: | Artificial Intelligence |
| Citations: | 339 - 35 self |
BibTeX
@ARTICLE{Kuipers00thespatial,
author = {Benjamin Kuipers and Rob Browning and Bill Gribble and Mike Hewett and Emilio Remolina},
title = {The Spatial Semantic Hierarchy},
journal = {Artificial Intelligence},
year = {2000},
volume = {119},
pages = {191--233}
}
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Abstract
The Spatial Semantic Hierarchy is a model of knowledge of large-scale space consisting of multiple interacting representations, both qualitative and quantitative. The SSH is inspired by the properties of the human cognitive map, and is intended to serve both as a model of the human cognitive map and as a method for robot exploration and map-building. The multiple levels of the SSH express states of partial knowledge, and thus enable the human or robotic agent to deal robustly with uncertainty during both learning and problem-solving. The control level represents useful patterns of sensorimotor interaction with the world in the form of trajectory-following and hill-climbing control laws leading to locally distinctive states. Local geometric maps in local frames of reference can be constructed at the control level to serve as observers for control laws in particular neighborhoods. The causal level abstracts continuous behavior among distinctive states into a discrete model ...
Keyphrases
spatial semantic hierarchy human cognitive map control level distinctive state partial knowledge ssh express state sensorimotor interaction control law multiple interacting representation large-scale space consisting hill-climbing control law local geometric map discrete model local frame particular neighborhood robot exploration robotic agent useful pattern multiple level causal level abstract continuous behavior
