The use of knowledge in open-ended systems
This work addresses the challenge of understanding knowledge dynamics in evolving systems for researchers in economics and evolutionary theory, though it appears incremental by extending static models to open-ended contexts.
The authors tackled the problem of modeling knowledge use and acquisition in open-ended evolutionary systems, where existing models are inadequate for contexts of innovative and unbounded change, and demonstrated results such as frame relativity and the ability for observers to agree to disagree.
Economists model knowledge use and acquisition as a cause-and-effect calculus associating observations made by a decision-maker about their world with possible underlying causes. Knowledge models are well-established for static contexts, but not for contexts of innovative and unbounded change. We develop a representation of knowledge use and acquisition in open-ended evolutionary systems and demonstrate its primary results, including that observers embedded in open-ended evolutionary systems can agree to disagree and that their ability to theorize about their systems is fundamentally local and constrained to their frame of reference what we call frame relativity. The results of our framework formalize local knowledge use, the many-selves interpretation of reasoning through time, and motivate the emergence of nonlogical modes of reasoning like institutional and aesthetic codes.