Reflective Systems Need Models at Run Time

We think that run-time models are a minimum necessity for significant self-awareness in Computationally Reflective systems. For us, a Computationally Reflective system is not only “self-aware” (it can collect information about its own behavior and that of its environment), but also “self-adaptive” (it can reason about that behavior and make adjustments that change it). Moreover, when the system is also “self-modeling”, that is, defined by the models it creates and maintains, then it can modify those models to better align its behavior with changes in its operating environment. In this paper, we show that building and managing these models presents some difficulties that are largely independent of the modeling mechanisms used. We also provide some mechanisms for coping with these difficulties, from a kind of “Behavior Mining” and “Model Deficiency Analysis” for current models to “Dynamic Knowledge Management”, of which major components are “Knowledge Refactoring” and “Constructive Forgetting”. None of these methods eliminate the problem, but each alleviates some of the difficult aspects of the problem, which allows bigger and more complex systems to exist in more complex and diverse environment for longer periods of time.