B. J. Kuipers. Representing Knowledge of Large-Scale Space. PhD thesis, Mathematics Department, Massachusetts Institute of Technology, Cambridge, Massachusetts, June 1977. Also MIT-AI TR-418, 1977.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....e j ) There are several studies that contain classifications of route instructions that might be used as a basis for a weighting function. For example, Denis et al. provide a model of idealized route instructions [18, 4] that might be used. Several other models, including Kuipers TOUR model [19, 20] and the PLAN model of Chown et al. 21] might yield di#erent weighting functions. In implementing the simplest path algorithm in this study, the weighting function described below follows Mark s original work [13] in which the weights were derived from the work of Streeter and coauthors [1, ....

Kuipers, B.: Representing Knowledge of Large-Scale Space. PhD thesis, Mathematics Department, Massachusetts Institute of Technology (1977) Technical Report 418, M.I.T. Artificial Intelligence Laboratory.

....[Note 15] 1 don t mean all this to seem pessimistic. It is not necessary, in understanding something, to have all one knows about it active in the mind at one time. One does need to have access to fragments of maps, at various levels of detail, of what one knows. The thesis of Kuipers [23], which proposes a theory of how a person s knowledge of a city might be represented in conaputational terms, might be re interpreted as a metaphor for how minds might deal with their own knowledge. Note 16] Theories. There is, I think. a special problem in making theories about the psychology ....

Kuipers, Benjamin. Representing Knowledge of Large-Scale Space. Ph.D. Thesis, M.I.T., Artificial Intelligence Laboratory, IA/TR-418. Cambridge, Ma., July 1978.

....a continuous environment to a discrete environment. This is the idea behind the spatial semantic hierarchy (Section 1.9) Kuipers and Byun (1988, 1991) demonstrate an engineered solution to the continuous to discrete abstraction problem for the NX robot. The target abstraction is the TOUR model (Kuipers, 1977, 1988) NX s distinctive places correspond to discrete states and its local control strategies implement the turn and travel actions. These constructs have to be manually redesigned in order to apply to a robot with a different sensorimotor apparatus. Kortenkamp Weymouth (1994) have engineered ....

Kuipers, B. J. (1977). Representing knowledge of large-scale space. Tech. Report TR-418, MIT Artificial Intelligence Laboratory, Cambridge, MA. Doctoral thesis, MIT Mathematics Department.

.... process (cf. Klein 82] Gluck remarks that the potential optimizing functions that are relevant for the wayfinding process are not restricted to minimal distance or even minimal effort (cf. Gluck 91] The wayfinding process in the TOUR model is a simple and slow approach to finding a way (cf. Kuipers 77] In the TRAVELLER model proposed by Leiser and Zilbershatz an incomplete wayfinding process is used which cannot find partial paths in the cognitive map (cf. Leiser Zilbershatz 89] We distinguish between the selection of a path that is known by experience (experiencebased wayselection) and ....

.... is used which cannot find partial paths in the cognitive map (cf. Leiser Zilbershatz 89] We distinguish between the selection of a path that is known by experience (experiencebased wayselection) and the search for a path by using a map (cf. Elliott Lesk 82] In the TOUR model (see cf. Kuipers 77] and in the TRAVELLER model (cf. Leiser Zilbershatz 89] experience based approach is focussed. Both models are based on a graph network which represents a mental model of the spatial environment and concentrate on how to integrate new knowledge about the external world into it. Leiser and ....

B. Kuipers. Representing Knowledge of Large-Scale Space. PhD thesis, MIT AI Lab, Cambridge, MA, 1977. TR-418.

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B. J. Kuipers. Representing Knowledge of Large-Scale Space. PhD thesis, Mathematics Department, Massachusetts Institute of Technology, Cambridge, Massachusetts, June 1977. Also MIT-AI TR-418, 1977.

....causal level theory and illustrate how to encode the minimality condition associated with this theory. We have implemented the program using Smodels [Niemel a and Simons, 1997] and confirm that the theory yields the intended models. 2 Related Work The SSH grew out of the TOUR model proposed in [Kuipers, 1977, Kuipers, 1978] Other computational theories of the cognitive map have been proposed: Kortenkamp et al. 1995, McDermott and Davis, 1984, Leiser and Zilbershatz, 1989, Yeap, 1988] These theories share the same basic principles: the use of multiple frames of reference, qualitative ....

B. Kuipers. Representing Knowledge of Large-Scale Space. PhD thesis, Artificial Intelligence Laboratory, MIT, 1977.

....causal level theory and illustrate how to encode the minimality condition associated with this theory. We have implemented the program using Smodels [Niemel a and Simons, 1997] and confirm that the theory yields the intended models. 2 Related Work The SSH grew out of the TOUR model proposed in [Kuipers, 1977, Kuipers, 1978] Other computational theories of the cognitive map have been proposed: Kortenkamp et al. 1995, McDermott and Davis, 1984, Leiser and Zilbershatz, 1989, Yeap, 1988] These theories share the same basic principles: the use of multiple frames of reference, qualitative ....

B. Kuipers. Representing Knowledge of Large-Scale Space.PhD thesis, Artificial Intelligence Laboratory, MIT, 1977.

....causal level theory and illustrate how to encode the minimality condition associated with this theory. We have implemented the program using Smodels [Niemel a and Simons, 1997] and confirm that the theory yields the intended models. 2 Related Work The SSH grew out of the TOUR model proposed in [Kuipers, 1977, Kuipers, 1978] Other computational theories of the cognitive map have been proposed: Kortenkamp et al. 1995, McDermott and Davis, 1984, Leiser and Zilbershatz, 1989, Yeap, 1988] These theories share the same basic principles: the use of multiple frames of reference, qualitative ....

B. Kuipers. Representing Knowledge of Large-Scale Space. PhD thesis, Artificial Intelligence Laboratory, MIT, 1977.

....Such a hierarchical topological map is clearly useful for finding routes in a large graph, though its structure may make it difficult to find optimal routes between arbitrary places. To use an abstraction hierarchy to find a usable route requires upward and downward mappings in the hierarchy [45, 46]. ffl Upward Mapping: a place at a lower level is mapped to the place corresponding to the abstraction region that contains it. ffl Downward Mapping: a hplace; path; diri tuple at the higher level is mapped to a corresponding hplace; path; diri tuple at the lower level. The downward mapping is ....

....is more complex than the upward mapping to reduce the inevitable ambiguity of inverting an abstraction relation. It is inspired by the relation between a limited access highway and the network of surface streets. Although the TOUR model includes a representation for this abstraction hierarchy [45, 46], there is as yet no theory of how the hierarchy is acquired. Spatial Semantic Hierarchy DRAFT: February 18, 2000 29 4.4 The TOUR Model The TOUR Model [45, 46, 47] structures the abduction as an incremental, opportunistic, spatially localized computation. It is organized around a set of fluents ....

[Article contains additional citation context not shown here]

B. J. Kuipers. Representing Knowledge of Large-Scale Space. PhD thesis, Mathematics Department, Massachusetts Institute of Technology, Cambridge, Massachusetts, June 1977. Also MIT-AI TR-418, 1977. Available via ftp://ftp.cs.utexas.edu/pub/qsim/papers/Kuipers-PhD-77.ps.gz.

....knowledge. Knowledge of large scale space (e.g. the cognitive map of a city (Lynch, 1960) is particularly accessible to study because the process of assimilating new information is constrained by the speed of physical travel, so states of partial knowledge are easily observable. The TOUR model (Kuipers, 1977,1978) is a computational model of the cognitive map, exhibiting a solution to the problem: How can local observations acquired during travel be assimilated into a structure that permits answering route finding and relative position questions The model consists of a number of different ....

....spatial features at different levels of detail. The observational input to the TOUR model is simulated as a sequence of partially specified travel instructions containing only information that could be acquired from a local observation. All other information is supplied by the assimilation process (Kuipers, 1977, 1978) While this permits subsequent acquisition of order and local geometry information (and thence the rest of the cognitive map) there remain easily observable phenomena for which no explanation can be stated in terms of this representation. 1. I can t tell you how I get there. I just know ....

Kuipers, B. J. (1977). Representing Knowledge of Large-scale Space (MIT Artificial Intelligence Laboratory TR-418). Doctoral dissertation, Department of Mathematics, MIT, Cambridge, MA.

....The structure of the SSH is largely independent of the specific sensors and effectors the agent has available, as long as the sensors detect sufficient distinctions among states, and the effectors move the agent continuously through the environment. The SSH extends and clarifies the TOUR Model [34, 35, 36, 41]. In many ways, the SSH can also be seen as extending and making precise the higher levels of Brooks subsumption architecture proposal as expressed in [7] and in the three level architectures [5, 10, 19] though not Brooks later ideas in [8] The four levels of the SSH are called the control, ....

....Such a hierarchical topological map is clearly useful for finding routes in a large graph, though its structure may make it difficult to find optimal routes between arbitrary places. To use an abstraction hierarchy to find a usable route requires upward and downward mappings in the hierarchy [34, 35]. ffl Upward Mapping: a place at a lower level is mapped to the place corresponding to the abstraction region that contains it. ffl Downward Mapping: a hplace; path; diri tuple at the higher level is mapped to a corresponding hplace; path; diri tuple at the lower level. The downward mapping is ....

[Article contains additional citation context not shown here]

B. J. Kuipers. Representing Knowledge of Large-Scale Space. PhD thesis, Mathematics Department, Massachusetts Institute of Technology, Cambridge, Massachusetts, June 1977. Also MIT-AI TR-418, 1977. Available via ftp://ftp.cs.utexas.edu/pub/qsim/papers/Kuipers-PhD-77.ps.gz.

....in any useful sense. Furthermore, the combinatorics of a complex environment are such that a complete understanding can only be obtained by factoring the sets of actions and sense impressions into manageable dimensions. Based on my earlier work on computational modeling of the human cognitive map [Kuipers 1977, 1978, 1979, 1983] I hypothesized that the best approach for the Critter was to emulate human learning of a spatial environment. This involves acquiring from observations gathered during travel, a model of the spatial structure of the environment expressed in several different representations of ....

....of observations into surrounds, places, and paths uses a data driven, opportunistic algorithm, implemented as a set of rules that examine the previous and current state of the Critter after each action. The state of the Critter (adapted from the You Are Here Pointer in the TOUR model [Kuipers 1977, 1978] is described in terms of its current sense vector, surround, place, path, orientation at place, and direction of travel on path. The orientation rules allow the state of the Critter to be filled out from information already in the cognitive map, and the assimilation rules extend the ....

B. J. Kuipers. 1977. Representing Knowledge of Large-Scale Space. Cambridge, MA: MIT Artificial Intelligence Laboratory TR-418.

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Benjamin J. Kuipers. Representing knowledge of large-scale space. Tech. Report TR-418, MIT Artificial Intelligence Laboratory, Cambridge, MA, July 1977. Doctoral thesis, MIT Mathematics Department.

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B. Kuipers, "Representing knowledge of large-scale space, Tech. Rep. 418, 1977. [Online]. Available: citeseer.ist.psu.edu/kuipers77representing.html

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B. J. Kuipers, "Representing knowledge of large scale space," Massachusetts Institute of Technology, Ph.D. Thesis, 1977.

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B. J. Kuipers, `Representing knowledge of large-scale space', Technical Report 418, (1977).

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