%Original file available from http://www.cs.odu.edu/~jbollen/bibliographies/bibtex/cogsci_AI.bib
%Last update: Saturday 18 January 2003
%Current number of entries: 6

@article{spatia:kuipers2000,
author = {B. Kuipers},
title = {The Spatial Semantic Hierarchy},
journal = {Artificial Intelligence},
volume = {119},
number = {1-2},
pages = {191--233},
month = {May},
year = {2000},
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 Tor control laws in particular neighborhoods. The causal level abstracts continuous behavior among distinctive states into a discrete model consisting of states linked by actions. The topological level introduces the external ontology of places, paths and regions by abduction to explain the observed pattern of states and actions at the causal level. Quantitative knowledge at the control, causal and topological levels supports a ''patchwork map'' of local geometric frames of reference linked by causal and topological connections. The patchwork map can be merged into a single global frame of reference at the metrical level when sufficient information and computational resources are available. We describe the assumptions and guarantees behind the generality of the SSH across environments and sensorimotor systems. Evidence is presented from several partial implementations of the SSH on simulated and physical robots. (C) 2000 Elsevier Science B.V. All rights reserved.},
keywords = {SPATIAL REASONING ; COGNITIVE MAP ; ROBOT EXPLORATION ; MAP LEARNING ;  QUALITATIVE REASONING ; MOBILE ROBOT NAVIGATION ; OBJECTS},
}



@BOOK{artifi:winston1984,
title = {Artificial Intelligence},
author = {Patrick Henry Winston},
year = 1984,
publisher = {Addison-Wesley},
address = {Reading, MA},
}



@BOOK{artifi:rich1983,
title = {Artificial intelligence},
author = {Elaine Rich},
publisher = {McGraw-Hill},
address = {New York},
year = 1983,
}




@BOOK{handbo:cohen1982,
title = {Handbook of Artificial Intelligence},
editor = {Paul R. Cohen and Edward A. Feigenbaum},
year = 1982,
publisher = {William Kaufman},
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volume = 3,
}



@BOOK{semant:minsky1968,
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title = {Semantic Information Processing},
year = 1968,
publisher = {MIT Press},
address = {Cambridge, MA},
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@BOOK{approa:ringland1998,
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  year = 1988,
  publisher = {Research Studies Press},
  address = {Letchworth, England},
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@BOOK{knowle:geldenhuys,
  author = {Aletta E. Geldenhuys and Hendrik O. {van Rooyen} and Franz Stetter},
  title = {Knowledge Representation and Relation Nets},
  year = {1999},
  publisher = {Kluwer Academic Publishers},
  address = {Boston, MA},
}