In 1948, the psychologist Edward Tolman described experiments in which rats were trained to follow a path through a complex maze to reach a food box. After the rats performed perfectly (chose the shortest way to reach the goal), the trained path was blocked; the rats had to select another path from a variety of alternatives. Astonishingly, most of the rats found a path that was close to the most direct connection to the food box, whereas not a single rat erroneously tried to follow the original path on which they had been trained. On the basis of these findings, Tolman argued the rats had “acquired not merely a strip-map . . . but, rather, a wider comprehensive map to the effect that the food was located in such and such a direction in the room” (p. 204). Tolman’s paper, entitled “Cognitive maps in rats and men,” marked the starting point of psychological spatial cognition research. Today there is a great body of evidence on how humans (and animals) learn routes, find ways, navigate through familiar and unknown environments, and on the strategies they use when they get lost. Contemporary research on robotics and AI is concerned with similar problems. For example, how must a mobile robot system be designed to improve its efficiency for tasks such as route choice and navigation? Certainly, the robot must acquire an internal representation of the environment – a cognitive map – and apply adequate procedures to plan movements. A related problem exists in the domain of geoinformatics. A geographic information system must be able to efficiently store, process, and retrieve geo-referenced data, i.e. data which is associated with locations defined in a geographic reference system. On the other hand, it should also interact with the user in a comprehensible way, that is, it should take the user’s mental representations of spatial knowledge into account. Applications such as location-based services, geovisualization or semantic information retrieval lead to an especially close interaction between human and machine reasoning. In the last years, a growing number of researchers from AI and robotics have addressed cognitive questions. Psychologists have become sensitive to the computational properties of robot navigation or issues of reasoning with diagrams and qualitative spatial representations. Research in this rapidly evolving interdisciplinary enterprise has a name: Spatial Cognition Research. Spatial Cognition: From Rat-Research to Multifunctional Spatial Assistance Systems
[1]
Bernd Krieg-Brückner,et al.
Modelling Navigational Knowledge by Route Graphs
,
2000,
Spatial Cognition.
[2]
Cornelius Hagen,et al.
Interactive Layout Generation with a Diagrammatic Constraint Language
,
2000,
Spatial Cognition.
[3]
Axel Lankenau,et al.
Selbstlokalisation in Routengraphen
,
2001,
AMS.
[4]
Max J. Egenhofer,et al.
Reasoning about Binary Topological Relations
,
1991,
SSD.
[5]
K. Sterelny.
The Imagery Debate
,
1986,
Philosophy of Science.
[6]
P. Johnson-Laird,et al.
Reasoning, Models, and Images: Behavioral Measures and Cortical Activity
,
2003,
Journal of Cognitive Neuroscience.
[7]
Wilfried Brauer,et al.
Spatial Cognition II, Integrating Abstract Theories, Empirical Studies, Formal Methods, and Practical Applications
,
2000
.
[8]
M. Knauff,et al.
Preferred mental models in qualitative spatial reasoning: A cognitive assessment of Allen's calculus
,
1995
.
[9]
Anthony G. Cohn,et al.
A Spatial Logic based on Regions and Connection
,
1992,
KR.
[10]
Reinhold Rauh,et al.
A Cognitive Assessment of Topological Spatial Relations: Results from an Empirical Investigation
,
1997,
COSIT.
[11]
Bernhard Nebel,et al.
On the Complexity of Qualitative Spatial Reasoning: A Maximal Tractable Fragment of the Region Connection Calculus
,
1999,
Artif. Intell..
[12]
E. Tolman.
Cognitive maps in rats and men.
,
1948,
Psychological review.
[13]
Kim Sterelny,et al.
The Imagery Debate
,
1991
.
[14]
C. Freksa,et al.
Spatial Cognition, An Interdisciplinary Approach to Representing and Processing Spatial Knowledge
,
1998
.
[15]
Bettina Berendt,et al.
Spatial Thinking with Geographic Maps: An Empirical Sstudy
,
1997,
Herausforderungen an die Wissensorganisation.