Qualitative Representation of Spatial KnowledgeThis book develops, for the first time, a qualitative model for the representation of spatial knowledge based only on locative relations between the objects involved. The core of this book is devoted to the study of qualitative inference methods that take into account the rich structure of space. These methods can be applied to quite a number of areas characterized by uncertain or incomplete knowledge, as for example geographic information systems, robot control, computer-aided architectural design, and natural language information systems. |
Contents
Introduction | 1 |
12 The problem and why it should be solved | 2 |
13 The kind of solution sought | 4 |
14 Overview | 5 |
Qualitativeness | 7 |
21 Qualitative vs quantitative knowledge | 8 |
23 Structured relational domains | 10 |
A cognitive perspective on knowledge representation | 13 |
524 Structure and table lookup | 68 |
525 The effect of multiple constraints | 69 |
531 Constraint satisfaction problem | 70 |
532 Consistency improvement | 71 |
533 Heuristics | 74 |
54 Exploiting the structure of space | 75 |
542 Abstract maps | 76 |
543 Propagation heuristics | 80 |
31 Issues in knowledge representation | 14 |
32 Knowledge representation model | 16 |
33 Modalities of representation | 19 |
331 The declarativeprocedural distinction | 20 |
333 The qualitativequantitative distinction | 22 |
34 Summary | 23 |
Qualitative representation of positions in 2D | 25 |
41 2D scenes | 26 |
412 Relevant dimensions | 28 |
42 Arrangement | 29 |
43 Topological relations | 33 |
431 Systematic derivation of topological relations | 34 |
433 Structure of the topological domain | 37 |
44 Orientation | 39 |
441 Systematic derivation of orientation relations | 40 |
442 Structure of the orientation domain | 43 |
443 Reference frames | 44 |
444 Objects with extension | 46 |
45 Examples | 51 |
46 Summary | 53 |
Reasoning with qualitative representations | 55 |
51 Transforming between frames of reference | 56 |
52 Composition of spatial relations | 61 |
522 Composition of orientation relations | 65 |
523 Composition of topologicalorientation pairs | 66 |
544 Constraint relaxation | 99 |
545 Coarse reasoning and hierarchical organization | 102 |
55 Summary | 103 |
Applications | 105 |
61 Building cognitive maps | 107 |
62 Visualization | 112 |
Extensions of the basic model | 117 |
72 Size | 118 |
73 Distance | 121 |
Relevant related work | 129 |
811 Interval algebras | 130 |
812 Cartesian tuples of relations | 132 |
813 Other relational approaches | 134 |
82 Other approaches to the representation of spatial knowledge | 140 |
822 Cognitive maps and route finding | 143 |
823 Linguistically motivated research | 145 |
824 Relational algebras | 146 |
Conclusion | 149 |
92 Future research issues | 150 |
93 Summary | 153 |
Composition tables for various special cases | 155 |
Bibliography | 165 |
| 193 | |
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abstract acceptance areas algorithm Allen's analogical Artificial Intelligence aspects chapter cognitive maps composition of relations composition tables computational overhead Computer concept Conference on Artificial constraint network constraint propagation constraint satisfaction constraint satisfaction problem contains context corresponding data structure defined deictic dependency network described dimension distance distinction editor Egenhofer example explicit Figure frame of reference Freksa given heuristics hierarchical implicit intersection intervals intrinsic orientation involved Kleer knowledge representation Kobler logical mechanisms Mukerjee natural language nodes Ø Ø Ø operations orientation relations overlapping pairs parent object physical point of view positional information positional relations primary object primitive Proceedings properties qualitative approach qualitative representations quantitative reference frame reference object relational domain relative position relevant relset representation of spatial represented world resulting scene shapes space spatial knowledge spatial prepositions spatial reasoning spatial relations Technische Universität München temporal tion topological and orientation truth maintenance system under-determined values variables visual
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