A biologically inspired working memory framework for robots
Joshua L. Phillips, David C. Noelle
- 发表年份
- 2006
- 引用次数
- 50
摘要
The human brain includes a capacity-limited memory system devoted to the short-term retention of task-relevant information. This system is called working memory. Some computational neuroscience accounts of working memory have explained it in terms of interactions between the prefrontal cortex and the mesolimbic dopamine system. Inspired by these models, we have constructed a software toolkit for creating working memory components for robot control systems, based on the proposed mechanisms used by the brain. We report our design for this toolkit, as well as the results of a feasibility study, involving a robotic version of the delayed saccade task, and we discuss future plans to test this framework in the context of more complex tasks.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991