DAML-based policy enforcement for semantic data transformation and filtering in multi-agent systems

Abstract

This paper describes an approach to runtime policy-based control over information exchange that allows a far more fine-grained control of these dynamically discovered agent interactions. The DARPA Agent Markup Language (DAML) is used to represent policies that may either filter messages based on their semantic content or transform the messages to make them suitable to be released. Policy definition, management, and enforcement are realized as part of the KAoS architecture. The solutions presented have been tested in the Coalition Agents Experiment (CoAX) - an experiment involving coalition military operations.