Tarek Richard Besold

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The integration of artificial intelligence (AI) within cognitive science (CogSci) necessitates further elaborations on, and modelings of, several indispensable cognitive criteria. We approach this issue by emphasizing the close relation between artificial general intelligence (AGI) and CogSci, and discussing, particularly, “rationality” as one of such(More)
The literature on conceptual blending and metaphor-making has illustrations galore of how these mechanisms may support the creation and grounding of new concepts (or whole domains) in terms of a complex, integrated network of older ones. In spite of this, as of yet there is no general computational account of blending and metaphor-making that has proven(More)
Concept blending, a cognitive process which allows for the combination of certain elements (and their relations) from originally distinct conceptual spaces into a new unified space combining these previously separate elements and allowing the performance of reasoning and inference over the combination, is taken as a key element of creative thought and(More)
In Cognitive Science, conceptual blending has been proposed as an important cognitive mechanism that facilitates the creation of new concepts and ideas by constrained combination of available knowledge. It thereby provides a possible theoretical foundation for modeling high-level cognitive faculties such as the ability to understand, learn, and create new(More)
Creativity is usually not considered to be a major issue in current AI and AGI research. In this paper, we consider creativity as an important means to distinguish human-level intelligence from other forms of intelligence (be it natural or artificial). We claim that creativity can be reduced in many interesting cases to cognitive mechanisms like(More)
During the 1980s Michie defined Machine Learning in terms of two orthogonal axes of performance: predictive accuracy and comprehensibility of generated hypotheses. Since predictive accuracy was readily measurable and comprehensibility not so, later definitions in the 1990s, such as that of Mitchell, tended to use a one-dimensional approach to Machine(More)