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Its awkward title refers to Mr Kahneman's two-tier model of cognition: "System 1" is quick, intuitive and responsible for the quirks and mistakes described above (and many others).
Augmented cognition, in contrast, focuses on deducing a cognitive state with the aim of somehow enhancing it.So when someone is overwhelmed with information, an augmented cognition system would try to help him cope by diverting some of it.
In these works, each visual cognition system is treated as a scoring system which assigns a score to each of the partitioned intervals in the common visual space.
In our previous work [27, 28], it has been demonstrated that combination of two visual cognition system using the CFA framework can improve each of the individual systems.
In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells.
By extending a visual cognition system to become a scoring system based on each of the statistical means M 1, M 2, and M 3 respectively, the problem of combining visual cognition systems is transformed to the problem of combining multiple scoring systems.
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In summary, our CFA framework provides two criteria: performance ratio and cognitive diversity to guide us to combine two visual cognition systems with confidence radii.
Then the problem of combining visual cognition systems is transformed to the problem of combining multiple scoring systems.
Section 2 of this paper discusses two methods of combining visual cognition systems: statistical mean and combinatorial fusion.
Based on these means, scoring systems p and q are constructed from the two visual cognition systems P and Q, respectively, in Sect.
Combination of these two visual cognition systems and analysis of the combination for the data set is discussed in more detail in Sect.
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Justyna Jupowicz-Kozak
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