War is always evolving, becoming more complex over time. With the addition of new technologies and emerging threats the complexity on the battlefield is also growing. Following this trend tools to train new recruits or develop new doctrines also becomes more complex. One of the tools impacted by this is military wargaming. While wargaming is an ancient practice it has developed to follow the growing complexities of war. In the context of military training wargames portray multi-domain battlefield containing artillery, helicopters, tanks, infantry, planes, terrain and much more. To keep the wargames significant and executable the implementation of AI into military wargames was explored. This proved to have an impact on aspects such as data processing, decision making and strategies. Further research shows that while possible and useful the implementation of AI into military wargaming is of an ad hoc nature and lacks any guidance or standardization. That is why this thesis set out to develop a practical and guiding framework for wargame developers for the implementation of AI into military wargaming.

After an exploratory literature review the knowledge gap is identified in the crossing between AI, wargaming and their integration. This lead to the main research question being “Which framework can guide wargame developers in the field of AI and military wargaming through the implementation process ?”. To answer this main research question several sub questions are developed and answered using several research methods.

The first sub question is: “What are the current challenges and constraints in the implementation of AI into military wargaming and how can they be addressed? This question is answered in chapter one with the use of a literature review. It results in more depth into the problem and more insight into the knowledge gap.

The second sub question is: “What are the requirements, that the framework aims to achieve?” This question is answered in chapter two with the use of another literature review and expert interviews. This resulted in three design principles and several requirements. The principles, requirements and their sources can be found in table 4. Furthermore, the result of the expert interviews highlighted the value of a supplementary method, when academic literature is not abundant.

The third sub question is: “How can the design principles and requirements be translated into a framework?” Based on the requirements a preliminary framework is developed. This framework is than tested with a use case to find areas of improvement. The use case was a validation implementation of AI into the military wargame called “Take That Hill”. This resulted in a framework consisting of several phases and activities. The result can be seen in figure 7. Furthermore, the outcome of the use case illustrated the wargame is not properly balanced as it can be won by simply always moving forward. In addition to the direct relation between the requirements and the translation into the framework another finding took place. The use case illustrated the importance of testing the preliminary framework. As the use case uncovered a new dimension in the framework with the core activities, which were not apparent from the theory alone.

The last sub question is: “What is validity of the designed framework?”. This was answered by assessing whether the requirements were met and expert interviews. The requirements assessment can be found in table 6 and the final version of the framework can be found in figure 8. Furthermore, while the validation expert interviews directly improved the framework they also showed the importance of the diversity of experts interviewed. The experts for the requirements focused on time and security, while the experts for the validation focused on the ethical and moral aspects of AI in military wargaming.

In conclusion, this thesis presents a multidisciplinary approach to solving a problem in military training and doctrine development. The development of an practical and guiding framework for AI implementation in military wargaming represents a significant advancement in the field, offering both academic contributions and practical applications. By aligning with the goals of the Master’s program in Complex Systems Engineering and Management, this research exemplifies the integration of complex and complicated domains, ultimately contributing to the enhancement of military preparedness and operational effectiveness.

As this thesis was written as part of a graduation internship at TNO the research recommends the wargame developers of TNO to use this framework as a guide during future implementations of AI into military wargaming and expend on the framework when necessary.