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A model for learning and imprinting with finite and infinite memory range
| Content Provider | Semantic Scholar |
|---|---|
| Author | Pfaffelhuber, Ernst |
| Copyright Year | 2004 |
| Abstract | A generalization of the Bush-Mosteller learning model, in the sense of a response strength rationale, can simulate both a finite and an infinite memory range and describe learning as well as imprinting processes, the latter being characterized by the property that earlier observations enter with more weight into the system's response tendencies than later ones. The resulting difference equation for the response probabilities is no longer time invariant. Optimality properties of the model are discussed, in particular with respect to probability learning. Carnap's inductive probabilities are shown to provide a least mean square estimate for a stationary stochastic environment. |
| Starting Page | 229 |
| Ending Page | 236 |
| Page Count | 8 |
| File Format | PDF HTM / HTML |
| DOI | 10.1007/BF00270576 |
| Alternate Webpage(s) | https://page-one.springer.com/pdf/preview/10.1007/BF00270576 |
| PubMed reference number | 4718023 |
| Alternate Webpage(s) | https://doi.org/10.1007/BF00270576 |
| Journal | Medline |
| Volume Number | 12 |
| Journal | Kybernetik |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
