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A Framework for Modelling Approximate Decision Making
| Content Provider | Semantic Scholar |
|---|---|
| Author | Car, Adrijana |
| Copyright Year | 2000 |
| Abstract | This work is based on the idea to use different levels of hierarchical shortest path computations to approximate decision making and potentially missing information. E.g., a set of shortest paths determined in a full network would represent a person with perfect information and decision making capability such as a taxi driver or local resident. Systematic reduction of the original graph would model less and less perfect information, and consequently the decision making. Such an approach allows for reasoning to be simpler at levels with fewer details, challenging the selection of relevant data for an analytical task. Consideration of the main principles for the design of hierarchies useful as such a selection mechanism, raises a number of theoretical and practical research questions related to spatial information. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.giscience.org/GIScience2000/posters/138-Car.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
