Abstract
In this paper we continue our investigation on the viability of Answer Set Programming (ASP) as a tool for formalizing, and reasoning about, psychological models. In the field of psychology, a considerable amount of knowledge is still expressed using only natural language. This lack of a formalization complicates accurate studies, comparisons, and verification of theories. We believe that ASP, a knowledge representation formalism allowing for concise and simple representation of defaults, uncertainty, and evolving domains, can be used successfully for the formalization of psychological knowledge. In previous papers we have shown how ASP can be used to formalize a rather well-established model of Short-Term Memory, and how the resulting encoding can be applied to practical tasks, such as those from the area of human-computer interaction. In this paper we extend the model of Short-Term Memory and introduce the model of a substantial portion of Long-Term Memory, whose formalization is made particularly challenging by the ability to learn proper of this part of the brain. Furthermore, we compare our approach with various established techniques from the area of cognitive modeling.
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Balduccini, M., Girotto, S. (2011). ASP as a Cognitive Modeling Tool: Short-Term Memory and Long-Term Memory. In: Balduccini, M., Son, T.C. (eds) Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning. Lecture Notes in Computer Science(), vol 6565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20832-4_24
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DOI: https://doi.org/10.1007/978-3-642-20832-4_24
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