Abstract
One area of intense focus in Artificial Intelligence (AI) research is to implement intelligent agents and machines that can think, reason, and solve problems with similar if not better proficiency than humans. The advancements in our understanding of intelligence and its governing principles have lead researchers to explore vastly different and passionately debated approaches to building intelligent systems. However, in recent years a consensus appears to be emerging, as observed by the 2013 AAAI Fall Symposium on Integrated Cognition, where an initial proposal is for a standard model of human-like minds. This model is largely based on current state-of-the-art cognitive architectures, such as ACT-R, Sigma and Soar. While we do not disagree with the proposed model, we believe more computer science based theories for modeling human-like minds should be considered for modeling memory and recognition functions. In this paper, we present a survey of the current literature that supports our position.
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Brooks, T.N., Kamruzzaman, A., Leider, A., Tappert, C.C. (2019). A Computer Science Perspective on Models of the Mind. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_57
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