14 DAY TRIAL // One of the most important aspects that separates our minds from the processors that power computers is the fact that we can go about solving routine or complex problems using our innate creativity, whereas machines cannot. Researchers are now working on ways of emulating the human mind.
Humans are especially good at resolving “insight” problems in this manner, as in issues that require large volumes of “lateral” knowledge, spanning other fields of research than the one the problem proper addresses.
Recently, investigators have set forth a new explanation for how humans are capable of doing so. The idea comes with equations and mathematical formulations aimed at helping experts incorporate this new theory into artificial intelligence (AI) programs.
In other words, it could be that the new explanation will provide researchers with a direction to peddle on in creating computers that emulate the way of thinking of the human mind.
According to Rensselaer Polytechnic Institute (RPI) professor of cognitive science Ron Sun, AI research could be considerably advanced if the “Explicit-Implicit Interaction Theory” is properly applied to computers.
Details of the proposal appear in the July issue of the scientific journal Psychological Review, in a paper called “Incubation, Insight, and Creative Problem Solving: A Unified Theory and a Connectionist Model.”
“As a psychological theory, this theory pushes forward the field of research on creative problem solving and offers an explanation of the human mind and how we solve problems creatively,” the scientist explains.
“But this model can also be used as the basis for creating future artificial intelligence programs that are good at solving problems creatively,” the expert goes on to say.
Sun authored the new paper with colleague Sèbastien Hèlie, who is based at the University of California in Santa Barbara (UCSB). The cognitive architecture the team proposes is called CLARION, and the journal entry contained all mathematical specifications needed to set it up.
This is basically a computer software that can act liked a cognitive system. In some key aspects related to creative problem-solving, the CLARION system and human test subjects performed similarly.
“The simulation data matches the human data very well,” Sun says of the system's performances.
He adds that humans generally go through four stages In solving problems creatively – preparation, incubation, insight (illumination), and verification.
Explicit-Implicit Interaction (EII) theory “unifies a lot of fragmentary pre-existing theories,” the team leader goes on to say.
“These pre-existing theories only account for some aspects of creative problem solving, but not in a unified way. EII unifies those fragments and provides a more coherent, more complete theory,” he concludes.