| Автор | Jing Peng |
| Автор | Williams, Ronald, J. |
| Дата выпуска | 1993 |
| dc.description | Sutton's Dyna framework provides a novel and computationally appealing way to integrate learning, planning, and reacting in autonomous agents. Examined here is a class of strategies designed to enhance the learning and planning power of Dyna systems by increasing their computational efficiency. The benefit of using these strategies is demonstrated on some simple abstract learning tasks. |
| Издатель | Sage Publications |
| Тема | reinforcement learning |
| Тема | dynamic programming |
| Тема | sequential decision problems |
| Название | Efficient Learning and Planning Within the Dyna Framework |
| Тип | Journal Article |
| DOI | 10.1177/105971239300100403 |
| Print ISSN | 1059-7123 |
| Журнал | Adaptive Behavior |
| Том | 1 |
| Первая страница | 437 |
| Последняя страница | 454 |
| Аффилиация | Jing Peng, Northeastern University |
| Аффилиация | Williams, Ronald, J., Northeastern University |
| Выпуск | 4 |
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