Suvojit is a Senior Data Scientist at DunnHumby. He enjoys exploring new and innovative ideas and techniques in the field of AI and tries to solve real-world machine learning problems by thinking out of the box. He writes about the latest advancements in Artificial Intelligence and Natural Language processing. You can follow him on LinkedIn. The media shown in this article is not owned by Analytics Vidhya and are used at the Author's discretion

One major limitation of current cognitive architectures is that models are typically constructed in an "empty" architecture, and that the knowledge specifications (typically production rules) are specific to the particular task. This means that general executive control strategies have to be implemented for each specific model, which means a lack of consistency and constraint. Alternatively, they are implemented as part of the architecture itself, which is often implausible, because strategies are learned and differ among individuals. The alternative is to assume executive control consists of strategies that can transfer from one task to another. The PRIMs theory (Taatgen 2013) provides a modeling framework for this transfer. The approach is discussed using the example of working memory control.