Applying Intent-Sensitive Policy to Automated Resource Allocation: Command, Communication and Most Importantly, Control

Keywords: policy representation, policy conformance metrics, AIC, multi-user policies

Abstract: As battlefield communications technologies have begun to achieve their potential, the notion of ‘winning the information war’ has begun to take on a new complexion—one in which we may be our own biggest enemy. A fundamental problem is that the overhead costs and complexity associated with deciding how to allocate information resources—including generation, processing and routing resources—are too high in an environment where human decision and guidance resources are already overstressed.

We are developing an approach that enables commanders to specify policy that will inform an automated communications resource management system. This policy represents the commander’s intent for the allocation of communications resources during the execution of a mission; the policy takes the form of a set of general and specific statements about the priorities, constraints and objectives for information flow. We view this policy as central to any problem in which a decision-maker wishes to precisely guide the behavior of a resource allocation actor. As such, policy has utility in complex domains ranging from cockpit display space to refinery operations. Our approach is called IPSO-FACTO—Intuitive Policy Specification for Optimized Flow of Asynchronous C3I Transmissions in Operations. IPSO-FACTO addresses problems including: suitable representations of policy, policy conformance metrics, adaptive information allocation, multi-user policies, and semi-automated policy construction.

We have implemented a prototype version of the IPSOFACTO system (that does not yet incorporate this taskbased policy derivation) and are currently evaluating it. Initial results show that the policy representation we have provided is very expressive, but time consuming and error prone to generate directly. Nevertheless, policy created in such a fashion does enable human control of automated resource allocation algorithms and can improve the performance of such resource allocation dramatically.