Name
Abstract | ||
|---|---|---|
If artificial neural networks are ever to form the foundation for higher level cognitive behaviors in machines or to realize their full potential as explanatory devices for human cognition, they must show signs of autonomy, multifunction operation, and intersystem integration that are absent in most existing models. This model begins to address these issues by integrating predictive learning, sequence interleaving, and sequence creation components to simulate a spectrum of higher-order cognitive behaviors which have eluded the grasp of simpler systems. Its capabilities are described based on simulations calling for increasing levels of functionality and are used to show how the model can progress from fundamental sequence learning and recall tasks to sophisticated behaviors such as an ability to solve simple mathematical expressions and a creative capacity for the formation and application of inductive rules. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/s11023-007-9085-z | Minds and Machines |
Keywords | Field | DocType |
Predictive learning,Memory interleaving,Creativity,Inductive reasoning,Autonomous neural networks | Inductive reasoning,Predictive learning,GRASP,Expression (mathematics),Computer science,Cognitive science,Artificial intelligence,Artificial neural network,Cognition,Creativity,Sequence learning | Journal |
Volume | Issue | ISSN |
18 | 1 | 0924-6495 |
Citations | PageRank | References |
2 | 0.47 | 18 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steve Donaldson | 1 | 3 | 1.84 |