Page 125 - Deep Learning
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108                         Creativity

            instrumental in producing it. If a unit P is involved in generating a result or
            outcome R through option O, and R is evaluated negatively, then the activation
            of O is decreased. If alternative options Oʹ, Oʹʹ, …, are available in P, and if the
            person continues to attend to the problem, the balance among the options is
            altered. O will eventually lose out to some competing option even though O
            was preferred initially.
               The  change  in  P  propagates  upward  through  the  layers  of  processing,
            potentially  causing  a  qualitative  change  in  the  problem  representation  in
            working memory. This in turn alters the distribution of activation over mem-
            ory, which might cause potentially useful but hitherto unheeded knowledge
            elements to be retrieved. The ultimate consequence is that the heuristic search
            process moves through a different solution space.
               The core of this redistribution theory of insight is a specification of the
            exact conditions under which the process of responding to negative feedback
            with gradually lowered activation levels will produce a qualitative change in the
            problem representation. Consider a choice point (processing unit) in the visual
            system  with,  for  example,  three  different  outbound  options.  The  argument
            proceeds through six hypotheses that jointly constitute sufficient conditions
            for insight; that is, for the involuntary and unexpected passage of a previously
            unheeded option into consciousness after a period without progress.
               First, each choice point is associated with a certain amount of activation.
            To a first approximation, the amount of activation can be thought of as the
            sum of the activations contributed by the inputs to the unit. This assumption
            is familiar from network theories of all kinds.
               Second, the activation associated with a choice point is distributed across
            its  outbound  links  (options)  in  proportion  to  their  relative  strengths.  The
            strength of an option measures past experience; more precisely, it is propor-
            tional to the frequency with which that option has been executed, how often it
            has been associated with success or failure, the expected payoff if it is executed,
            the estimated cost or effort of execution and perhaps other variables as well.
            The strength determines the proportion of activation allocated to an option
            when the choice point is active.
               Third, there is a threshold such that when the activation associated with a
            choice point is distributed over the outbound options, some options might rise
            above threshold, while others remain below. Options that are above thresh-
            old pass activation and information – the result of whatever computation the
            processing unit performs – onto the next processing layer. Options that receive
            a  level  of  activation  less  than  the  threshold  remain  dormant  or  unheeded.
            That is, neither activation nor information is passed along those links, nor is
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