Computer Assisted Wargame for Military Capability-Based Planning

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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Kingfish Ace: Application of Gaming to Help Air Force Leaders Understand Agile Combat Employment

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On Benchmarking and Validation in Wargames

“…Simulation and modelling: These tools are used to create virtual representations of battlefield scenarios and to predict the outcomes of different courses of action. Of the documents that remained in the SR, the future directions involved such subjects as Additional Research (Christensen & Dobias 2021), Adding additional complexity to the computer system being researched (Colbert, E, Sullivan & Kott 2017;Hodickỳ et al 2020), application of non-kinetic operation models to test suitability (D'Antonio et al 2014), the extended incorporation of AI and Machine Learning for better optimisation of processes (Davis & Bracken 2022;DeBerry et al 2021;Hart et al 2017), collecting data to better model real systems and incorporate a further collection of data in systems (Dewoody et al 2014;Ormrod et al 2019), and refining overall processes to improve performance (Guo & Sprague 2016).…”