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A Spatial Logic based on Regions and Connection
 PROCEEDINGS 3RD INTERNATIONAL CONFERENCE ON KNOWLEDGE REPRESENTATION AND REASONING
, 1992
"... We describe an interval logic for reasoning about space. The logic simplifies an earlier theory developed by Randell and Cohn, and that of Clarke upon which the former was based. The theory supports a simpler ontology, has fewer defined functions and relations, yet does not suffer in terms of its us ..."
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Cited by 565 (29 self)
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We describe an interval logic for reasoning about space. The logic simplifies an earlier theory developed by Randell and Cohn, and that of Clarke upon which the former was based. The theory supports a simpler ontology, has fewer defined functions and relations, yet does not suffer in terms of its useful expressiveness. An axiomatisation of the new theory and a comparison with the two original theories is given.
L.: Toward a Geometry of Common Sense: A Semantics and a Complete Axiomatization of Mereotopology
 in: IJCAI95
"... Mereological and topological notions of connection, part, interior and complement are central to spatial reasoning and to the semantics of natural language expressions concerning locations and relative positions. While several authors have proposed axioms for these notions, no one with the exception ..."
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Cited by 103 (0 self)
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Mereological and topological notions of connection, part, interior and complement are central to spatial reasoning and to the semantics of natural language expressions concerning locations and relative positions. While several authors have proposed axioms for these notions, no one with the exception of Tarski [18], who based his axiomatization of mereological notions on a Euclidean metric, has attempted to give them a semantics. We offer an alternative to Tarski, starting with mereotopological notions that have proved useful in the semantic analysis of spatial expressions. We also give a complete axiomatization of this account of mereotopological reasoning. 1
Qualitative Spatial Representation and Reasoning Techniques
, 1997
"... . The field of Qualitative Spatial Reasoning is now an active research area in its own right within AI (and also in Geographical Information Systems) having grown out of earlier work in philosophical logic and more general Qualitative Reasoning in AI. In this paper (which is an updated version o ..."
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Cited by 97 (9 self)
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. The field of Qualitative Spatial Reasoning is now an active research area in its own right within AI (and also in Geographical Information Systems) having grown out of earlier work in philosophical logic and more general Qualitative Reasoning in AI. In this paper (which is an updated version of [25]) I will survey the state of the art in Qualitative Spatial Reasoning, covering representation and reasoning issues as well as pointing to some application areas. 1 What is Qualitative Reasoning? The principal goal of Qualitative Reasoning (QR) [129] is to represent not only our everyday commonsense knowledge about the physical world, but also the underlying abstractions used by engineers and scientists when they create quantitative models. Endowed with such knowledge, and appropriate reasoning methods, a computer could make predictions, diagnoses and explain the behaviour of physical systems in a qualitative manner, even when a precise quantitative description is not available 1 ...
Calculi for Qualitative Spatial Reasoning
, 1996
"... . Although Qualitative Reasoning has been a lively subfield of AI for many years now, it is only comparatively recently that substantial work has been done on qualitative spatial reasoning; this paper lays out a guide to the issues involved and surveys what has been achieved. The papers is gener ..."
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Cited by 72 (9 self)
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. Although Qualitative Reasoning has been a lively subfield of AI for many years now, it is only comparatively recently that substantial work has been done on qualitative spatial reasoning; this paper lays out a guide to the issues involved and surveys what has been achieved. The papers is generally informal and discursive, providing pointers to the literature where full technical details may be found. 1 What is Qualitative Reasoning? The principal goal of Qualitative Reasoning (QR) [86] is to represent not only our everyday commonsense knowledge about the physical world, but also the underlying abstractions used by engineers and scientists when they create quantitative models. Endowed with such knowledge, and appropriate reasoning methods, a computer could make predictions, diagnoses and explain the behaviour of physical systems in a qualitative manner, even when a precise quantitative description is not available 1 or is computationally intractable. The key to a qualitative ...
Qualitative Simulation Based On A Logical Formalism Of Space And Time
 Proceedings AAAI92, AAAI Press, Menlo
, 1992
"... We describe an envisionmentbased qualitative simulation program. The program implements part of an axiomatic, first order theory that has been developed to represent and reason about space and time. Topological information from the modelled domain is expressed as sets of distinct topological ..."
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Cited by 56 (20 self)
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We describe an envisionmentbased qualitative simulation program. The program implements part of an axiomatic, first order theory that has been developed to represent and reason about space and time. Topological information from the modelled domain is expressed as sets of distinct topological relations holding between sets of objects. These form the qualitative states in the underlying theory and simulation. Processes in the theory are represented as paths in the envisionment tree. The algorithm is illustrated with an example of a simulation of phagocytosis and exocytosis  two processes used by unicellular organisms for garnering food and expelling waste material respectively. Introduction Envisionmentbased simulation programs used in Qualitative Reasoning (QR) are now well established. The notion of an envisionment originated in de Kleer's NEWTON program, but now appears as a central program design feature in many QR simulation programs  see Weld and de Kleer (1990)...
Spatiotemporal representation and reasoning based on RCC8
 In Proceedings of the seventh Conference on Principles of Knowledge Representation and Reasoning, KR2000
, 2000
"... this paper is to introduce a hierarchy of languages intended for qualitative spatiotemporal representation and reasoning, provide these languages with topological temporal semantics, construct effective reasoning algorithms, and estimate their computational complexity. ..."
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Cited by 55 (10 self)
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this paper is to introduce a hierarchy of languages intended for qualitative spatiotemporal representation and reasoning, provide these languages with topological temporal semantics, construct effective reasoning algorithms, and estimate their computational complexity.
A Qualitative Theory of Motion Based on SpatioTemporal Primitives
, 1998
"... This paper presents a formal theory for reasoning about motion of spatial entities, in a qualitative framework. Taking over a theory intended for spatial entities, we enrich it to achieve a theory whose intended models are spatiotemporal entities, an idea sometimes proposed by philosophers or ..."
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Cited by 55 (1 self)
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This paper presents a formal theory for reasoning about motion of spatial entities, in a qualitative framework. Taking over a theory intended for spatial entities, we enrich it to achieve a theory whose intended models are spatiotemporal entities, an idea sometimes proposed by philosophers or AI authors but never fully exploited. We show what kind of properties usually assumed as desirable parts of any spacetime theory are recovered from our model, thus giving a sound theoretical basis for a natural, qualitative representation of motion.
Qualitative Spatial Representation and Reasoning
 An Overview”, Fundamenta Informaticae
, 2001
"... The need for spatial representations and spatial reasoning is ubiquitous in AI – from robot planning and navigation, to interpreting visual inputs, to understanding natural language – in all these cases the need to represent and reason about spatial aspects of the world is of key importance. Related ..."
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Cited by 45 (6 self)
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The need for spatial representations and spatial reasoning is ubiquitous in AI – from robot planning and navigation, to interpreting visual inputs, to understanding natural language – in all these cases the need to represent and reason about spatial aspects of the world is of key importance. Related fields of research, such as geographic information science
Boolean Connection Algebras: A New Approach to the RegionConnection Calculus
 Artificial Intelligence
, 1999
"... The RegionConnection Calculus (RCC) is a well established formal system for qualitative spatial reasoning. It provides an axiomatization of space which takes regions as primitive, rather than as constructions from sets of points. The paper introduces boolean connection algebras (BCAs), and prove ..."
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Cited by 43 (7 self)
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The RegionConnection Calculus (RCC) is a well established formal system for qualitative spatial reasoning. It provides an axiomatization of space which takes regions as primitive, rather than as constructions from sets of points. The paper introduces boolean connection algebras (BCAs), and proves that these structures are equivalent to models of the RCC axioms. BCAs permit a wealth of results from the theory of lattices and boolean algebras to be applied to RCC. This is demonstrated by two theorems which provide constructions for BCAs from suitable distributive lattices. It is already well known that regular connected topological spaces yield models of RCC, but the theorems in this paper substantially generalize this result. Additionally, the lattice theoretic techniques used provide the first proof of this result which does not depend on the existence of points in regions. Keywords: RegionConnection Calculus, Qualitative Spatial Reasoning, Boolean Connection Algebra, Mer...
Imprecision in Finite Resolution Spatial Data
 GeoInformatica
, 1997
"... An important component of spatial data quality is the imprecision resulting from the resolution at which data are represented. Current research on topics such as spatial data integration and generalisation needs to be wellfounded on a theory of multiresolution. This paper provides a formal framewo ..."
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Cited by 43 (7 self)
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An important component of spatial data quality is the imprecision resulting from the resolution at which data are represented. Current research on topics such as spatial data integration and generalisation needs to be wellfounded on a theory of multiresolution. This paper provides a formal framework for treating the notion of resolution and multiresolution in geographic spaces. It goes further to develop an approach to reasoning with imprecision about spatial entities and relationships resulting from finite resolution representations. The approach is similar to aspects of rough and fuzzy set theories. The paper concludes by providing the beginnings of a geometry of vague spatial entities and relationships. Keywords: uncertainty, vagueness, rough set, fuzzy set, resolution, spatial reasoning, data quality 1. Introduction The notion of spatial resolution is fundamental to many aspects of the representation of spatial data, and a proper formulation of a multiresolution data model is...