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From Fitness Landscapes to Knowledge Landscapes (Oliver, Roos, 1999)
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The Case for Using Probabilistic Knowledge in a Computer Chess Program (John L. Jerz)
Resilience in Man and Machine

 
Based on the complexity theory concept of fitness landscapes, this article develops and discusses the concept of "knowledge landscapes." A knowledge landscape is metaphor of an ever-changing knowledge of each individual and organization. Each one of us is surrounded by potential knowledge landscape peaks and valleys. Individuals, communities, and organizations move on their own knowledge landscapes by simultaneously climbing local peaks and exploring other visible peaks. The higher one climbs, the harder it is to climb still further. The ability to climb is also limited by the identity, who we are, which on an organizational level is linked to the tightness of organizational interconnectedness. Co-evolutionary struggles between individuals and organizations can lead us to climb potential knowledge peaks faster. Moreover, our knowledge landscapes exist on many levels of scale, meaning what appears to be one peak is actually a series of sub-peaks on a smaller level of scale.

Systemic Practice and Action Research, Vol. 12.3, forthcoming June 1999.

p.7 Kauffman also draws the concept of co-evolution into a species’ climb up peaks on its fitness landscape. A co-evolutionary struggle can ensue between “predator” and “prey” species, in which the former develops a slightly better predation method that is subsequently countered by a new protection innovation by the latter, and so on. An example of a co-evolutionary struggle is the on-going battle between police and organized criminals to develop better new and innovative technologies to improve their ability to respectively prevent or commit crimes. As each group develops a new innovation, it alters the fitness landscape of the other- making a comfortable local peak appear to shrink. Door locks dating from the 1960s are swift work for thieves of today.

p.8 Jantsch (1980) advocates a co-evolutionary rather than rational approach to planning. According to Bettis and Prahalad (1995), organizations should always be prepared to “unlearn” their emergent “dominant logics”.

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