Name
Abstract | ||
|---|---|---|
We review the reasoning underlying two approaches to combination of sensory
uncertainties. First approach is noncommittal, making no assumptions about
properties of uncertainty or parameters of stimulation, as in Gepshtein,
Tyukin, and Albright (2010). Then we explain the relationship between this
approach and the one commonly used in modeling "higher level" aspects of
sensory systems, such as in visual cue integration, where assumptions are made
about properties of stimulation. The two approaches follow similar logic,
except in one case maximal *uncertainty* is minimized and in the other minimal
*certainty* is maximized. Then we demonstrate how optimal solutions are found
to the problem of resource allocation under uncertainty. |
Year | Venue | Keywords |
|---|---|---|
2010 | Clinical Orthopaedics and Related Research | resource allocation,visual cues,uncertainty principle,information theory,pattern recognition,sensory system |
Field | DocType | Volume |
Certainty,Uncertainty principle,Resource allocation,Artificial intelligence,Sensory system,Mathematics,Machine learning,Cue integration | Journal | abs/1007.0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergei Gepshtein | 1 | 7 | 3.10 |
| Ivan Tyukin | 2 | 71 | 9.53 |
| Thomas D. Albright | 3 | 0 | 0.34 |