A person's cognitive map, or knowledge of large-scale space, is built up from observations gathered as he travels through the environment. It acts as a problem solver to find routes and relative positions. as well as describing the current location. The TOUR model captures the multiple representations that make up the cognitive map, the problemsolving strategies, it uses, and the mechanisms for assimilating new information. The representations have rich collections of states of partial knowledge, which support many of the performance characteristics of common-sense knowledge. 1

A framework for the qualitative representation of positional information in a two-dimensional space is presented. Qualitative representations use discrete quantity spaces, where a particular distinction is introduced only if it is relevant to the context being modeled. This allows us to build a flexible framework that accommodates various levels of granularity and scales of reasoning. Knowledge about position in large-scale space is commonly represented by a combination of orientation and distance relations, which we express in a particular frame of reference between a primary object and a reference object. While the representation of orientation comes out to be more straightforward, the model for distances requires that qualitative distance symbols be mapped to geometric intervals in order to be compared; this is done by defining structure relations that are able to handle, among others, order of magnitude relations; the frame of reference with its three components (distance system, s...

Two studies invesligated updaling q[' se!f-position and heading dwinx real. imagined, wld simuh#ed locomotion. Snl/ects wel'e e.-los('d to (1 IWO-S(',k qHellt pttl]l with a titI'll between segnlentx.' they ,.ponded by tin'rang to,bee the ori,,in as they would if they had walked the path }nd were at the end ' the second stsment. The conalllions q['pathwG eA7oaw'e int htded physical walking. intaxined ,valking j)'om a verbal description. watchbtg another person wall and eperiencing optic flow that simulated walkinx. with or without a phys- ical turn between the path segments. tf .sldgects fitlied to npdaw an internal representation g' heading, but did encode tile pathway tl'ajeo tory. they xhottkl httve overturlcd hv the magnitltde 'the turn between the patJ segments. 5nch svslemalic overturnbig was ./bund in the description and watching comlitions, but not with physical walking. Simulated optic flow was not by itse'sttt'ient to induce spatial ttpdat- ing j/tat supported correct turn t'espon.cs+ An important component of navigation is updating knowledge of one's spatial position and orientation. People navigating on foot receive multiple cues for updating, Vision signals sclf-nolion by the changing positions of distal landmarks and by the optic flow teld. Proprioception (including veslibt, lar sensing as well as kines- hetic feedback from muscles. tendons. and joints) provides cues to the navigator's velocity and acceleration. In 1he research reported here, we asked how well people update heir inlernal representation of location and orientation as they rave[ in space under conditions in which these cues are reduced or unavailable, including conditions in which they do not physically move at all. The conditions examined included wafking without vision (proprioceplive cues...

. Research in Qualitative Reasoning builds and uses discrete symbolic models of the continuous world. Inference methods such as qualitative simulation are grounded in the theory of ordinary differential equations. We argue here that cognitive mapping --- building and using symbolic models of the large-scale spatial environment --- is a highly appropriate domain for qualitative reasoning research. We describe the Spatial Semantic Hierarchy (SSH), a set of distinct representations for space, each with its own ontology, each with its own mathematical foundation, and each abstracted from the levels below it. At the control level, the robot and its environment are modeled as a continuous dynamical system, whose stable equilibrium points are abstracted to a discrete set of "distinctive states." Trajectories linking these states can be abstracted to actions, giving a discrete causal graph level of representation for the state space. Depending on the properties of the actions, th...

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This dissertation presents a model of the knowledge a person has about the spatial structure of a large-scale environment: the "cognitive map." The functions of the cognitive map are to assimilate new information about the environment, to represent the current position, and to answer route-finding and relative-position problems. This model (called the TOUR model) analyzes the cognitive map in terms of symbolic descriptions of the environment and operations on those descriptions. Knowledge about a particular environment is represented in terms of route descriptions, a topological network of paths and places, multiple frames of reference for relative positions, dividing boundaries, and a structure of containing regions. The current position is described by the "You Are Here" pointer, which acts as a working memory and a focus of attention. Operations on the cognitive map are performed by inference rules which act to transfer information among different descriptions and the "You Are Here"...

The "Map in the Head" metaphor states that knowledge of largescale space is isomorphic to the information stored in a graphical map: That is, corresponding operations are used to store and retrieve information. The purpose of this essay is to look carefully at the "Map in the Head" metaphor to see the limits of its applicability. There are two types of experimental results that are difficult to accommodate within this metaphor. First, instead of being integrated into a single map, spatial knowledge can fall into disconnected components, with little or no relation between the components. Second, knowledge of routes (and other spatial facts) may be represented asymmetrically, so that a route can be followed in one direction but not in the other. The first set of results leads us to replace the simple "Map in the Head" with a more complex and sophisticated metaphor including separate metrical and topological components. The second set of results suggests that even the more sophisticated "...

There have been some straightforward efforts to extend Allen's interval-based temporal logic to spatial dimensions by using Cartesian tuples of relations [6]. We take a different approach based on a study of the kind of information that best relates two entities in 2-dimensional space qualitatively. The relevant spatial categories turn out to be "projection" and "orientation". We define a small set of spatial relations and stress the importance of making their reference frames explicit. Furthermore, we introduce "abstract maps", an analogical representation that inherently reflects the structure of the represented domain, and demonstrate their use in spatial reasoning. This scheme also facilitates "coarse" reasoning and the hierarchical organization of knowledge. These representational issues form the basis for an experimental system to develop "cognitive maps" from 2-D scanned layout plans of buildings. 1 Introduction Cognitive spatial concepts are qualitative in nature. Despite the ...

Abstract. We argue that a comprehensive model of graph comprehension must include spatial cognition. We propose that current models of graph comprehension have not needed to incorporate spatial processes, because most of the task/graph combinations used in the psychology laboratory are very simple and can be addressed using perceptual processes. However, data from our own research in complex domains that use complex graphs shows extensive use of spatial processing. We propose an extension to current models of graph comprehension in which spatial processing occurs a) when information is not explicitly represented in the graph and b) when simple perceptual processes are inadequate to extract that implicit information. We apply this model extension to some previously published research on graph comprehension from different labs, and find that it is able to account for the results. 1

Nearly forty years ago, Kevin Lynch (1960) described the environmental image in terms of five structural features: districts, edges, paths, nodes, and landmarks. Though the work has been much criticized, even by Lynch himself, it may provide a basis for a computational tool useful both in design and in research on spatial cognition. This paper revisits Lynch's responses to criticisms as a means of ascertaining the potential merit of the prototypical tool, called "WayMaker." In addressing Lynch's concerns about his own method and results, we see that WayMaker and tools like it may support Lynch's value of participatory design, while enabling extension of his efforts to understand how people think about the spaces they inhabit. The paper includes discussion of methods for research in spatial cognition and potential use of WayMaker within graphical environments supporting virtual communities.