Name
Abstract | ||
|---|---|---|
Given a set of stimuli presenting views of some environment, how can one characterize the natural modules or "objects" that compose the environment? Should a given set of items be encoded as a collection of instances or as a set of rules? Res-tricted formulations of these questions are addressed by analysis within a new mathematical framework that describes stochastic parallel computation. An algorithm is given for simulating this computation once schemas encoding the modules of the environ-ment have been selected. The concept of computational tempera-ture is introduced. As this temperature is lowered, the system appears to display a dramatic tendency to interpret input, even if the evidence for any particular interpretation is very weak. |
Year | Venue | Field |
|---|---|---|
1983 | AAAI | Inference,Computer science,Theoretical computer science,Artificial intelligence,Modular design,Schema (psychology),Machine learning,Encoding (memory),Computation |
DocType | Citations | PageRank |
Conference | 7 | 12.48 |
References | Authors | |
1 | 1 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul Smolensky | 1 | 215 | 93.76 |