Innovation as emergence: Hybrid agent enablers for evolutionary competence

Human-performed innovation processes can be viewed as complex adaptive systems in their own right. The competitive effectiveness of such innovation processes is of not only academic interest, but also in commercial and military domains, in which levels of competency in innovation spell the difference between success and failure for the competitors.This paper describes an epigenetic view of innovation as an interaction of innovation agents, domain systems, and models of those systems. As contrasted from a genetic algorithms framework, we instead examine the case in which multiple localized innovation agents that include humans or hybrid human-machine agents are in interaction with evolving models of target systems.Key enablers of this framework include (1) system patterns (emergent, configurable, evolvable models) and (2) innovation agent views. The resulting framework can improve understanding of human-performed innovation processes, as well as point out enablers of increased competency for the overall system of innovation.