| Автор | Szepesvári, Csaba |
| Автор | Lórincz, Andràs |
| Дата выпуска | 1993 |
| dc.description | A brain model-based alternative to reinforcement learning is presented that integrates artificial neural networks and knowledge-based systems into one unit or agent for goal-oriented problem solving. The agent may possess inherited and learned artificial neural networks and knowledge-based subsystems. The agent has and develops ANN cues to the environment for dimensionality reduction (data compression) to ease the problem of combinatorial explosion. Here, a dynamical concept model is put forward that builds cue models of the phenomena in the world, designs dynamical action sets (concepts), and makes them compete in a spreading-activation neural stage to reach decision. The agent works under closed-loop control. Here we examine a simple robotlike object in a two-dimensional conditionally probabilistic space. |
| Издатель | Sage Publications |
| Тема | adaptivity |
| Тема | artificial neural networks |
| Тема | knowledge-based system; self-organization |
| Тема | activation spreading |
| Тема | autonomous system |
| Название | Behavior of an Adaptive Self-organizing Autonomous Agent Working with Cues and Competing Concepts |
| Тип | Journal Article |
| DOI | 10.1177/105971239300200202 |
| Print ISSN | 1059-7123 |
| Журнал | Adaptive Behavior |
| Том | 2 |
| Первая страница | 131 |
| Последняя страница | 160 |
| Аффилиация | Szepesvári, Csaba, Jànos Bolyai Institute of Mathematics |
| Аффилиация | Lórincz, Andràs, Hungarian Academy of Sciences |
| Выпуск | 2 |
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