KMARF: A Framework for Knowledge Management and Automated Reasoning

In this paper, we present a generic framework for knowledge management and automated reasoning (KMARF) as an enabler for intelligent adaptive systems. KMARF targets multiple reasoning problem classes (such as planning, veri€cation and optimization) that can share the same underlying system state representation. Œe idea behind KMARF is to automatically select an appropriate problem solver based on a formalized reasoning expertise in the knowledge base, and convert a problem de€nition to a problem solver-readable format. Automation of the reasoning process reduces operational costs and enables the system to operate in dynamic environment conditions. We demonstrate our approach using a transportation planning use case.

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