Name
Abstract | ||
|---|---|---|
This paper presents a generic Bayesian map and shows how it is used for the development of a task done by an agent arranged in an environment with uncertainty. This agent interacts with the world and is able to detect, using only readings from its sensors, any failure of its sensorial system. It can even continue to function properly while discarding readings obtained by the erroneous sensor/s. A formal model based on Bayesian Maps is proposed. The Bayesian Maps brings up a formalism where implicitly, using probabilities, we work with uncertainly. Some experimental data is provided to validate the correctness of this approach. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11504894_47 | IEA/AIE |
Keywords | Field | DocType |
data fusion | Data mining,Spatial intelligence,Autonomous agent,Computer science,Correctness,Model-based reasoning,Formal specification,Sensor fusion,Artificial intelligence,Bayesian statistics,Machine learning,Bayesian probability | Conference |
Volume | ISSN | ISBN |
3533 | 0302-9743 | 3-540-26551-1 |
Citations | PageRank | References |
3 | 0.46 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fidel Aznar Gregori | 1 | 17 | 5.31 |
| Mar Pujol López | 2 | 4 | 1.82 |
| R. Rizo | 3 | 51 | 14.90 |