LAUSR

In the field of Artificial Intelligence (AI), efforts to achieve human-like behavior have taken very different paths through time. Cognitive Architectures (CAs) differentiate from traditional AI approaches, due to their intention to model cognitive and behavioral processes by understanding the brain’s structure and their functionalities in a natural way. However, the development of distinct CAs has not been easy, mainly because there is no consensus on the theoretical basis, assumptions or even purposes for their creation nor how well they reflect human function. In consequence, there is limited information about the methodological aspects to construct this type of models. To address this issue, some initial statements are established to contextualize about the origins and directions of cognitive architectures and their development, which help to outline perspectives, approaches and objectives of this work, supported by a brief study of methodological strategies and historical aspects taken by some of the most relevant architectures to propose a methodology which covers general perspectives for the construction of CAs. This proposal is intended to be flexible, focused on use-case tasks, but also directed by theoretic paradigms or manifestos. A case study between cognitive functions is then detailed, using visual perception and working memory to exemplify the proposal’s assumptions, postulates and binding tools, from their meta-architectural conceptions to validation. Finally, the discussion addresses the challenges found at this stage of development and future work directions.