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Policies are being increasingly used for automated system manage- ment and controlling the behavior of complex systems, allowing administrators to modify system behavior without changing source code or requiring the con- sent or cooperation of the components being governed. Past approaches to pol- icy representation have been restrictive in many ways. By way of contrast, se- mantically-rich policy representations can reduce human error, simplify policy analysis, reduce policy conflicts, and facilitate interoperability. In this paper, we compare three approaches to policy representation, reasoning, and enforcement. We highlight similarities and differences between Ponder, KAoS, and Rei, and sketch out some general criteria and properties for more adequate approaches to policy semantics in the future.

Semantic Web Languages for Policy Representation and Reasoning: A Comparison of KAoS, Rei, and Ponder