R. Rajagopalan and B. Kuipers. Qualitative spatial reasoning about objects in motion: application to physics problem solving. San Antonio, TX, March 1994. IEEE Conference on Artificial Intelligence for Applications (CAIA-94).  Home/Search   Document Details and Download   Summary   Related Articles   Check

....geometry. Very little work has been done on motion in such a qualitative framework. Even works done under the banner of socalled qualitative physics usually make use of the classical quantitative model of kinematics. Motion is thus usually represented in a Newtonian Cartesian framework [Rajagopalan and Kuipers, 1994] , Hays, 1989] Other studies focus more on related aspects, for instance [Forbus, 1983, Davis, 1989] insist more on the concept of dynamic process, and [Shanahan, 1995, Hartley, 1992] on default reasoning in metric spaces that are not really clearly characterized. Motion is nonetheless a key ....

R. Rajagopalan and B. Kuipers. Qualitative spatial reasoning about objects in motion: application to physics problem solving. San Antonio, TX, March 1994. IEEE Conference on Artificial Intelligence for Applications (CAIA-94).

.... for time and space is the basis of modern pre relativist physics, along with the assumption they are both dense (but see [13] for a physicist s dissident opinion) It is moreover used in robotics, and in a qualitative way in most work done under the label qualitative reasoning ( 10] 12] 11] [34]) mostly qualitative kinematics. It has also been used for a representation of motion verbs properties in [20] although the cognitive adequacy of such primitives is doubtful. Relative space is indeed advocated in most linguistically and or cognitively oriented work ( 39] 2] 22] but it ....

R. Rajagopalan and B. Kuipers. Qualitative spatial reasoning about objects in motion: application to physics problem solving. San Antonio, TX, March 1994. IEEE Conference on Artificial Intelligence for Applications (CAIA-94).

....over space and time. One of the major limitations of today s systems, for example, is that they capture only a snapshot of reality, reliant as they are on databases that contain only current data [ Hornsby and Egenhofer, 2000] 1 based on classical quantitative models of kinematics (see e.g. Rajagopalan and Kuipers, 1994; Hays, 1989 ] surprisingly little has been done to design qualitative spatio temporal representation formalisms [ Vieu, 1991; Galton, 1997; Muller, 1998; Hornsby and Egenhofer, 2000; Wolter and Zakharyaschev, 2000b ] let al..one implementations. More refs Or fewer Although a deep ....

R. Rajagopalan and B. Kuipers. Qualitative spatial reasoning about objects in motion: application to physics problem solving. In N. Guarino, editor, Proceedings of IEEE Conference on Artificial Intelligence for Applications (CAIA'94), volume 46. San Antonio, 1994.

....spatial simulation work of [145] based on the QSIM system [180] 5.1.2. Qualitative Motion Inspite of a large amount of work in mereo topological theories as a basis for common sense reasoning, very little work has been done on motion in a qualitative framework. Representation of motion as in [146, 112] is in a Newtonian Cartesian framework. Some work [75, 49] insist more on the concept of dynamic processes; elsewhere [163, 109] there is research on default reasoning in metric spaces that are not really clearly characterized. Motion is nevertheless a key notion in our understanding of spatial ....

Rajagopalan, R. and Kuipers, B.: \Qualitative spatial reasoning about objects in motion: application to physics problem solving", IEEE Conf. on AI for Applications,San Antonio, TX, 1994.

....geometry. Very little work has been done on motion in such a qualitative framework. Even works done under the banner of socalled qualitative physics usually make use of the classical quantitative model of kinematics. Motion is thus usually represented in a Newtonian Cartesian framework [Rajagopalan and Kuipers, 1994] , Hays, 1989] Other studies focus more on related aspects, for instance [Forbus, 1983, Davis, 1989] insist more on the concept of dynamic process, and [Shanahan, 1995, Hartley, 1992] on default reasoning in metric spaces that are not really clearly characterized. Motion is nonetheless a key ....

R. Rajagopalan and B. Kuipers. Qualitative spatial reasoning about objects in motion: application to physics problem solving. San Antonio, TX, March 1994. IEEE Conference on Artificial Intelligence for Applications (CAIA-94).

....representation, and illustrating their use to solve problems from two application areas, natural language understanding and the qualitative simulation of physical systems. More specifically, our methods have been applied to solve qualitative textbook problems [76] from the magnetic fields domain [68, 75, 71], and to solve problems in understanding natural language descriptions of an urban scene [70, 73] The magnetic fields problems are solved through qualitative simulation, and 9 ffl Diagram: ffl Text: Figure 13 shows an inclined wooden track that passes, for part of its length, through a strong ....

....the student s knowledge of the fundamental properties of magnetic fields. Since they all ask the student to describe what happens as a given event occurs, we solve the problems through qualitative simulation. This dissertation has made contributions in the area of qualitative spatial reasoning [68, 75, 71] and the area of integration of natural language and visual processing [74, 69, 73] Together, the techniques we have developed have allowed us to implement the first spatial reasoning system that starts with a diagram and text description of the initial state of a problem, and automatically ....

R. Rajagopalan and B. Kuipers. Qualitative spatial reasoning about objects in motion: Application to physics problem solving. In Proc. 10th IEEE Conf. on Aritificial Intelligence for Applications, San Antonio, TX, March 1994.

....assertions or a set of frames, slots, and values. In the current implementation, the Algernon knowledge representation language [Cra90, CK92] is used to maintain the knowledge base. We are using the Figure Understander as the input processing module in a magnetic fields problem solving system [RK94]. Our approach is motivated by the observation that a figure is a communication act involving at least two agents [Gri75] ffl The author of a figure has the goal of communicating a description of a situation to a human reader. ffl The reader of the figure has the goal of extracting the ....

....is then attached to the internal object description. In addition, we determine such things as the connectivity of the diagram object, the orientation of the object with respect to the global coordinate system, and the relative position of the object with respect to other objects in the diagram [Raj93, RK94]. The connectivity of a polygon is stored by creating knowledge base structures for all the edges and vectors, and storing the connections between the edges and vertices. The orientation of an object is described in terms of its extremal points: the rightmost, leftmost, topmost, and bottommost ....

Rajagopalan R., and B. Kuipers. Qualitative Spatial Reasoning about Objects in Motion: Application to Physics Problem Solving. In: Proceedings of the Tenth IEEE Conference on Artificial Intelligence for Applications (CAIA-94), San Antonio, Texas, March 1994.

....performs of the task of determining the current spatial state, determines what dynamic changes are taking place, and detects significant changes in the qualitative spatial state as they occur. We are using these models in a problem solving system which reasons about the effects of magnetic fields [Rajagopalan and Kuipers 93a] Our implementation architecture will also permit us to inherit any advances in the underlying systems, QPC and QSIM, such as the ability to incorporate incomplete quantitative information into the models [Kay and Kuipers 93] 2 A Spatial Representation Based on Extremal Points Figures 1 and 2 ....

Rajagopalan R., and B. Kuipers. Qualitative Spatial Reasoning about Objects in Motion: Application to Physics Problem Solving. Manuscript submitted to CAIA-94, San Antonio, Texas.

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