The term
Cognition refers to the mental action or process of acquiring knowledge and
understanding through thought, experience and the senses. Modeling refers to
the process of devising a representation, especially a mathematical one.
Collectively, Cognitive modeling deals with simulating problem solving and
other mental tasks in a computerized model. I believe that two important questions would
have flashed your mind after reading the definition of cognitive modeling.
First: Assuming that it is possible to imitate the task process of human brain,
what is the prospective of cognitive modeling from application point of view?
Second: How are the cognitive models
represented (i.e. how does it actually work?).
Cognitive
modeling is being used in different artificial intelligence application
especially neural networks, robotics and virtual reality. It plays a crucial
role in the development of futuristic applications which can be programmed in
such a way that the application will be capable enough to imitate or rather
predict human perception and react correspondingly. It provides support for
large scale decision making especially for the marketing and sales sector.
Currently, Cognitive models are commonly found in Computer games (making it
more interactive and realistic). Example of a system that uses cognitive modelling:
an intelligent tutoring system for school children which can gradually increase
the retention capacity of a student by analysis and feedback.
Cognitive models
are generally represented as mathematical models. Mathematical model refers to
a set of equations which takes a set of input to produce the corresponding
output. Consider the discrepancy detection application. According to Discrepancy
Detection Principle, recollections are more likely to change if a person does
not immediately detect discrepancies between misinformation and memory for the
original event. At times people recognize a discrepancy between their memory and
what they are being told. People might recollect, "I thought I saw a stop
sign, but the new information mentions a yield sign, I guess I must be wrong,
it was a yield sign." Although the individual recognizes the information
as conflicting with their own memories they still adopt it as true. If these
discrepancies are not immediately detected they are more likely to be
incorporated into memory. To avoid/remove such discrepancies from a statistical
data set, a classifier (a set of equations which when provided with the input
will be able to classify/identify the inconsistent data points in space)
cognitive model.
It is amazing
how much can be accomplished using cognitive modeling. It is a hot topic that
is under extensive research. We can expect a lot of applications which uses the
cognitive model in the near future.
Note: I’m not an
expert in Cognitive modeling. The blog article was just an outcome of my passionate
interest towards the subject. If you find any corrections, please let me know.
Stay tuned for
more.
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