Human-like Math Capability
Humans often solve arithmetic problems the "long way". The optimal
bit-based methods of the computer are not natural and, as such, not
employed by humans. Several psychological experiments have been
performed showing that, not only are the arithmetic operations used
by humans not optimal, but the long-hand algorithms can be suboptimal
and sometimes inconsistent. Some humans classify problems before
approaching them (even the classifications can be inconsistent) and
use a personal method that varies consistently with the class of
problem.
Kurt VanLehn
argues that a non-Last-In, First-Out (LIFO) goal
reconstruction technique can reproduce this behavior. An essential
component to the reproduction of this behavior is that goals cannot
be managed by a LIFO stack. VanLehn's Teton
architecture was designed specifically to model these types of behaviors.
Additionally, the
Soar architecture has also been applied
to the cognitively-plausible solution of math problems.
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Current Location: Common Descriptions - Capabilities - Human-Like Mathematical Reasoning