Abstract
Capability-based planning as an approach to defense planning is an almost infinitely complex engineered system with countless nodes and layers of interdependency, influenced by state and non-state diplomatic activities, information, military and economic actions creating secondary and third order effects. The main output of capability-based planning is the set of capability requirements needed to achieve the expected end-state. One revitalized qualitative technique that allows us to gain insights into unstructured and fuzzy problems in the military is wargaming—in its simplest form this involves manual wargaming. At the same time, there has been a push to bring computer assistance to such wargaming, especially to support umpire adjudication and move more generally towards full automation of human elements in wargames. However, computer assistance in wargaming should not be pushed, regardless of cost, towards quantitative techniques. The objective complexity of a problem often does not allow us to replicate the operational environment with the required fidelity to get credible experimental results. This paper discusses a discovery experiment aiming to verify the concept of applying a qualitative expert system within computer assisted wargaming for developing capability requirements in order to reduce umpire bias and risk associated with their decisions. The innovation here lies in applying system dynamics modelling and simulation paradigms when designing the theoretical model of capability development, which forms the core of the expert system. This new approach enables qualitative comparisons between different sets of proposed capability requirements. Moreover, the expert system allows us to reveal the effects of budget cuts on proposed capability requirement solutions, which the umpire was previously unable to articulate when comparing individual solutions by relying solely on his own knowledge. Players in the wargame validated the proposed concept and suggested how the study might be developed going forward: namely, by enabling users to define their own capabilities and not being limited by a predefined set of capabilities.
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