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- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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Qualitative Spatial Reasoning with Topological Relations in the Situation Calculus
- 2006
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Ingår i: Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, Melbourne Beach, Florida, USA, May 11-13, 2006. - : AAAI Press. - 9781577352617 ; , s. 713-718
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Konferensbidrag (refereegranskat)abstract
- We use a qualitative theory of spatial change and illustrate some of the key representational aspects of specifying such a theory using a formalism to reason about action & change; an effort that we regard to be essential toward a general integration of qualitative spatial reasoning with reasoning about the dynamic, causal aspects of spatial change. A topological theory of space, namely the region connection calculus, is used as the spatial metaphor in this work; the reason here primarily being that topological distinctions are inherently qualitative in nature and also because a relational approach as general as the RCC is representative of a similar class of relational techniques in the QSR domain. As such, our results can be easily generalised over a wide range of calculi, encompassing other aspects of space, that are based on similar semantics. The main aim of this paper is to illustrate first ideas on how a causal perspective to qualitative spatial reasoning may be provided using the situation calculus, which is a formalism to reason about dynamically changing domains, The minimalist notions of space and/or spatial dynamics in this paper are based on the hypothesis that it is imperative to approach the problem of the said integration at a elementary level before a higher-level abstraction involving complex actions & events is developed.
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| 2. |
- Hansson, Karin, et al.
(författare)
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Implementation of a Decision Theoretical Framework : A case study of the Red River Delta in Vietnam
- 2006
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Ingår i: Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference. - Menlo Park, CA : AAAI Press. - 9781577352617 ; , s. 824-
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We describe an application and implementation of a decision framework developed for selection of flood management strategies. It concerns developing countries in particular. The framework is developed to provide policy support and advice about water governance to meet demands at national, local, and river basin levels and can be of assistance as a tool for hazard management. The components in this framework are a simulation module interlinked with a decision module. The tool helps to analyse complex decisions that contain large degrees of uncertainty and number of interconnections.
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| 3. |
- Sundgren, David, et al.
(författare)
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Some Second Order Effects on Interval Based Probabilities
- 2006
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Ingår i: Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference. - Menlo Park, California : AAAI Press. - 9781577352617 ; , s. 848-853
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Konferensbidrag (refereegranskat)abstract
- In real-life decision analysis, the probabilities and values of consequences are in general vague and imprecise. One way to model imprecise probabilities is to represent a probability with the interval between the lowest possible and the highest possible probability, respectively. However, there are disadvantages with this approach, one being that when an event has several possible outcomes, the distributions of belief in the different probabilities are heavily concentrated to their centers of mass, meaning that much of the information of the original intervals are lost. Representing an imprecise probability with the distribution’s center of mass therefore in practice gives much the same result as using an interval, but a single number instead of an interval is computationally easier and avoids problems such as overlapping intervals. Using this, we demonstrate why second-order calculations can add information when handling imprecise representations, as is the case of decision trees or probabilistic networks. We suggest a measure of belief density for such intervals. We also demonstrate important properties when operating on general distributions. The results herein apply also to approaches which do not explicitly deal with second-order distributions, instead using only first-order concepts such as upper and lower bounds.
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