PAXsims is pleased to present a selection of recently-published items on simulation and serious gaming. Some of these may not address conflict, peacebuilding, or development issues at all, but have been included because of the broader perspective they offer on games-based education or analysis. Others might address “gaming-adjacent” issues such as group dynamics and decision-making, assessment, forecasting, or related topics. If you have published something recently and we haven’t yet included it, let us know!
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How do you get students to engage in a historical episode or era? How do you bring the immediacy and contingency of history to life? Michael A. Barnhart shares the secret to his award-winning success in the classroom with Can You Beat Churchill?, which encourages role-playing for immersive teaching and learning. Combating the declining enrollment in humanities classes, this innovative approach reminds us how critical learning skills are transmitted to students: by reactivating their curiosity and problem-solving abilities.
Barnhart provides advice and procedures, both for the use of off-the-shelf commercial simulations and for the instructor who wishes to custom design a simulation from scratch. These reenactments allow students to step into the past, requiring them to think and act in ways historical figures might have. Students must make crucial or dramatic decisions, though these decisions need not align with the historical record. In doing so, they learn, through action and strategic consideration, the impact of real individuals and groups of people on the course of history.
There is a quiet revolution underway in how history is taught to undergraduates. Can You Beat Churchill? hopes to make it a noisy one.
Malicious cyber activities are increasing worldwide and getting increasingly more sophisticated. Individuals, businesses, and governments explore different ways of tackling this development, for example, through developing policies to counter or mitigate cyber threats. One promising instrument for doing so is cybersecurity ex- ercises. Different cybersecurity exercises (e.g., red team/blue team exercises, cyber wargames, workshops, tabletop exercises, and simulations) can address different audiences and goals – from examining technical responses by critical infrastruc- ture providers to assessing diplomatic responses to a cyber incident. To grasp the potential of cybersecurity exercises – particularly for policy work – it is important to explore the different types of exercises in more detail.
The paper first highlights defining features of each cybersecurity exercise type to emphasize each type’s advantages. Workshops, for example, are speculative, collab- orative, and can improve understanding between different actors. Meanwhile, simu- lations can replicate reality as much as possible using digital networks, which helps simulate attacks and the reactions to such attacks. Secondly, the different exercise types are applied to different stages of the policy cycle – a cycle mapping policy work from defining a problem to the implementation and evaluation of a policy – to explore reasons for using them at certain stages of policy work. Simulations, for ex- ample, are particularly beneficial to use when implementing or evaluating a policy, for example, for testing its effectiveness.
The paper creates a simple guide for exploring the potential application of cyberse- curity exercises for policy work and for strategically using them. It is recommended to go through a three-step process to find whether cybersecurity exercises are an instrument to be used for a specific policy objective.
1) Firstly, scope out the policy work – consider the policy work at hand and the target audience to be reached.
2) Secondly, identify the stage of use – identify where the policy work is best situat- ed on the policy cycle.
3) Thirdly, consider the defining features of cybersecurity exercise types and identify which exercise type is the best to achieve the policy work goal.
Ultimately, the paper highlights that cybersecurity exercises are an instrument that decision-makers should consider when developing cybersecurity policies and/or aiming to achieve different cybersecurity policy goals.
Current wargaming techniques are effective training and research instruments for military scenarios with fixed tools and boundaries on the problem. Control cells composed of officiants adjudicating and evaluating moves enforce these boundaries. Real-world crises, however, unfold in several dimensions in a chaotic context, a condition requiring decision-making under deep uncertainty. In this article, we assess how pedagogical exercises can be designed to effectively capture this level of complexity and describe a new framework for developing deeply immersive exercises. We propose a method for designing crisis environments that are dynamic, deep, and decentralized (3D). These obviate the need for a control cell and enhance the usefulness of exercises in preparing military and policy practitioners by better replicating real-world decision-making dynamics. This paper presents the application of this 3D method, which integrates findings from wargame and negotiation simulation design into immersive crisis exercises. We share observations from the research, design, and execution of “Red Horizon,” an immersive crisis exercise held three times at Harvard University with senior civilian and military participants from multiple countries. It further explores connections to contemporary trends in international relations scholarship.
his research presents the wargaming commodity course of action automated analysis method (WCCAAM) – a novel approach to assist wargame commanders in developing and analyzing courses of action (COAs) through semi-automation of the military decision making process (MDMP). MDMP is a seven-step iterative method that commanders and mission partners follow to build an operational course of action to achieve strategic objectives. MDMP requires time, resources, and coordination – all competing items the commander weighs to make the optimal decision. WCCAAM receives the MDMP’s Mission Analysis phase as input, converts the wargame into a directed graph, processes a multi-commodity flow algorithm on the nodes and edges, where the commodities represent units, and the nodes represent blue bases and red threats, and then programmatically processes the MDMP steps to output the recommended COA. To demonstrate its use, a military scenario developed in the Advanced Framework for Simulation, Integration, and Modeling (AFSIM) processes the various factors through WCCAAM and produces an optimal, minimal risk COA.
The Prussian Kriegsspiel was the very first professional wargame and was originally introduced in the Prussian army in 1824 but has so far seen very little systematic research. This research project has compiled a corpus from all the rulesets currently extant, which was then made subject to formal and linguistic analysis. This yielded results in three important areas: First, by comparing them with a collection of contemporary texts on military theory it was possible to identify Kriegsspiel rulesets as distinctive text types. Second, comparing the rulesets gave valuable insights into the developmental history of the Kriegsspiel. And finally, it was possible to distinguish three distinctive phases in the development of the Kriegsspiel.
Effective cybersecurity risk management hinges on a strategic blend of people, processes, and technology working together to recognize and prevent attacks; mitigate and minimize negative impacts should attacks succeed; and resume operations after recovery. Ideally, risk management involves processes that engage the entire organization continually and holistically—not just episodic reactions by a few key personnel in times of crisis. The translation of lessons learned into implemented and validated improvements may be a missing or underutilized best practice. This chapter explores ways gaming can be used as a complement to authoritative standards and frameworks to optimize an organization’s cybersecurity posture and preparedness. A variety of gamified approaches are described and presented as useful tools with differentiating value at multiple stages in an ongoing cybersecurity risk management cycle. State-of-the-practice exemplars and successes are cited as are approaches to adapting games to both assess and improve an organization’s cybersecurity posture. The chapter concludes with some speculations about how games focused on cybersecurity can be expected to evolve and gain greater traction for risk management in light of emergent technologies and increasingly complex threat and defense landscapes.
Wargame is a simulated military operation with certain rules, specifications, and procedures, in which soldiers can virtually and indirectly experience the war. The ROK Navy operates the Cheonghae model, a training wargame model for helping commanders and staff master the procedures for conducting the war. It is important for commanders, staff and analysts to know whether a warship can perform its missions and how long it can last during a war. In existing model, the Cheonghae, the probability of kill of a warship is calculated simply considering the number of tonnage without any stochastic elements, and the warship’s mission availability is also determined based on predetermined values. With this model, it is difficult to get a value of the probability of kill that makes sense. In this dissertation, the author has developed a probabilistic model in which the warship vulnerability data of ROK-JMEM can be used. A conceptual model and methodology that can evaluate the mission performance of personnel, equipment, and supplies has been proposed. This can be expanded to a comprehensive assessment of wartime warship loss rates by integrating damage rates for personnel, equipment, and supplies in wartime.
National security and defense professionals have long utilized wargames to better understand hypothetical conflict scenarios. With conflict in the cyber domain becoming a more prominent piece in wargames in the national security community, this issue brief seeks to identify the common pathologies, or potential pitfalls, of cyber wargaming. It argues that the inherent turbulence of the cyber domain and segmented knowledge about cyber weapons negatively affect three components of cyber wargaming: the scenario development, the data usability, and the cross-participant comprehensibility. The brief offers some initial solutions to these problems, but, ultimately, the purpose of identifying pathologies is to prepare designers to meet these challenges in each unique design.
Opponent modeling is a significant method in imperfect information games. And intention recognition is regarded as the important but difficult in opponent modeling. This paper focuses on the task of tactical intention recognition in computational wargame. We propose an approach to recognize opponents’ intention which models the intention as long-term trajectories. The approach consists of situation encoding model and position prediction model. The first model uses attention mechanism to attach the statistic map data with dynamic feature and adopt CNN to learn the representation of battlefield situation. The position prediction model then predicts the long-term trajectories of opponents, based on well-represented situation vectors. Experiment indicates that our approach is proven to be effective on the task of tactical intention recognition in wargame. Meanwhile, a high-quality replay data set for analyzing the actions’ characteristics is also provided in this paper.
ScienceCampus doctoral researcher Jon-Wyatt Matlack explores the significance of computer games in shaping imaginations of the past. Focusing on Hearts of Iron IV, he considers how the format can encourage revision of the Nazi past, going against the grain of efforts towards critical Vergangenheitsbewältigung, or working through the past. The article explores how gamers can take up positions perpetuating the myth of a clean Wehrmacht while perpetuating narratives of a barbarian Eastern Europe where the USSR poses the greatest threat to humanity. He shows how reconstructions of historical narratives in digital spaces deserve more critical interrogation as a medium for the production of counterfactual history, especially given how popular and successful they are as depictions of the past, albeit a counterfactual one that draws on players’ affective urges and distorts historical reality.
The current requirements for CWMD preparedness across all levels of the Joint Forc- es have led to focused initiatives in the realm of nuclear weapons defense planning, training and exercise1. Techniques like military wargaming for putting such initiatives into action are of critical importance to addressing the centralized concepts of nuclear defense and deterrence. Conventional Nuclear Integration (CNI), a concept referring to the side- by-side operation of nuclear and conventional forces referenced by Kinman2, is a field of nuclear defense strategy that includes nuclear weapons employment on the battlefield. Though not always expressly grouped under the umbrella of CNI, military wargame ex- ercises which could be considered within the subset of CNI have provided insights into operations on the nuclear battlefield since the Cold War era.
After a decade of crisis, the EU now routinely uses futures meth- ods to anticipate the unexpected. Its aim is to address its blind spots. This paper details our experience of designing a foresight exercise to help EU diplomats face up to one of the most ingrained types of blind spot: a taboo issue. But our experience showed instead the dangers of such exercises. Far from needing encour- agement to address a taboo, our target audience wanted an excuse to do so, reflecting a shift to a more “geopolitical EU.”
Strategic foresight exercises are designed to help participants recognize their cognitive biases. But the more policymakers adopt them as routine, the more they use them to reinforce their existing aims. Simply: they learn to manipulate outcomes.
To prevent cheating, experts introduced adversarial elements, where colleagues paired off against one another. Competition was meant to inject new thinking into policy and break up bureaucratic hierarchies. In fact, these too reinforced old biases.
Table-top exercises (TTXs) are now the go-to tool, adopted by the EU: rather than competing, participants play as a single team. Collaboration encourages the kind of “risky- shifty” behavior which policymakers need in order to drop old shibboleths.
Complex Systems in which humans play a role, namely Human-Integrated Complex Systems (HICS), can be difficult to model or simulate due to the uncertainty introduced by the human component. Traditional modeling approaches such as physics-based modeling do not provide predictive insight towards situation awareness and management. War game designers, and game architects are familiar with HICS problem spaces, and use gamification of such complex contexts as a means of modeling human behavior to inform, predict, and manage an HICS style problem. The game play thereby becomes a means of providing situation awareness and management of the HICS by using human action during game play as a heuristic for pruning the intractable possibility space of the problem at large into a likely probability subspace based on the actions players actually take when playing an HICS game simulation. This paper explores the approach of gamification of real-world HICS problem spaces for situation awareness and management. A gamification methodology is introduced and investigated through the use case of military acquisitions.
The accurately program of search&rescue of the wounded is designed and an initial design idea of various subsystems is proposed in order to provide theoretical explorations and solutions for making the search & rescue of the wounded on a land battlefield immediate, intelligent and accurate and for lowering the death and disability rates of the wounded. A full combination of skill features and functional advantages is made between BDS and Armored ambulance, which is systematically applied to the search & rescue on the land battlefield. The rationality and feasibility of the program of search&rescue are guaranteed by functional combinations, comprehensive integration and experimental verification. The verification of the program of search&rescue is made in the form of war-game exercises. The result finds that the “BDS + Armored ambulance” pattern of search & rescue can accurately acquire real-time locations of the wounded, immediately provide on-site first-aid services and emergency aid & treatment for the wounded and rapidly receive and transfer the wounded, which demonstrate a better practice and application prospect of health services. As the BDS-3 is to be put into service in 2020, the informationized upgrading and transformation of Armored ambulance will be gradually completed and the “BDS+ Armored ambulance” program of search &rescue will exert a more obvious influence on the search & rescue of the wounded on the land battlefield, which provide a capability support for realizing the idea of “Medical Treatment be with Soldiers”.
The Simon Fraser University Faculty of Health Sciences ran course HSCI 486—Global Perspectives on the coronavirus disease 2019 (COVID-19) Pandemic—for fourth year undergraduates in the fall of 2020. The course instructors designed the course to culminate in a class game to expose undergraduate students to a complex public health decision-making environment. A game was developed by the author in consultation with the class instructors to allow teams of students to make policy decisions as the governments of neighbouring countries facing a pandemic similar in nature to COVID-19. The game was set on a fictional continent with fictional countries which nevertheless shared some characteristics of certain real countries. The game was supported by a spreadsheet model to evaluate player decisions, which was kept as simple as possible to create believable behaviours without seeking to be an accurate simulation. The game was successfully run in a 3-hour class and received very positive feedback from both students and instructors.
This thesis explores fog of war concepts through three submitted journal articles. The Department of Defense and U.S. Air Force are attempting to analyze war sce- narios to aid the decision-making process; fog modeling improves realism in these wargame scenarios. The first article “Navigating an Enemy Contested Area with a Parallel Search Algorithm”  investigates a parallel algorithm’s speedup, compared to the sequential implementation, with varying map configurations in a tile-based wargame. The parallel speedup tends to exceed 50 but in certain situations. The sequential algorithm outperforms it depending on the configuration of enemy loca- tion and amount on the map. The second article “Modeling Fog of War Effects in AFSIM”  introduces the Fog Analysis Tool (FAT) for the Advanced Framework for Simulation, Integration, and Modeling (AFSIM) to introduce and manipulate fog in wargame scenarios. FAT integrates into AFSIM version 2.7.0 and scenario results ver- ify the tool’s fog effects for positioning error, hits, and probability affect the success rate. The third article “Applying Fog Analysis Tool to AFSIM Multi-Domain CLASS scenarios”  furthers the verification of FAT to introduce fog across all warfighting domains using a set of Cyber Land Air Sea Space (CLASS) scenarios. The success rate trends with fog impact for each domain scenario support FAT’s effectiveness in disrupting the decision-making process for multi-domain operations. The three ar- ticles demonstrate fog can affect search, tasking, and decision-making processes for various types of wargame scenarios. The capabilities introduced in this thesis support wargame analysts to improve decision-making in AFSIM military scenarios.
We demonstrate an innovative framework (CoEvSoarRL) that lever- ages machine learning algorithms to optimize and simulate a re- silient and agile logistics enterprise to improve the readiness and sustainment, as well as reduce the operational risk. The CoEv- SoarRL is an asymmetrical wargame simulation that leverages re- inforcement learning and coevolutionary algorithms to improve the functions of a total logistics enterprise value chain. We address two of the key challenges: (1) the need to apply holistic predic- tion, optimization, and wargame simulation to improve the total logistics enterprise readiness; (2) the uncertainty and lack of data which require large-scale systematic what-if scenarios and analysis of alternatives to simulate potential new and unknown situations. Our CoEvSoarRL learns a model of a logistic enterprise environ- ment from historical data with Soar reinforcement learning. Then the Soar model is used to evaluate new decisions and operating conditions. We simulate the logistics enterprise vulnerability (risk) and evolve new and more difficult operating conditions (tests); meanwhile we also coevolve better logistics enterprise decision (solutions) to counter the tests. We present proof-of-concept results from a US Marine Corps maintenance and supply chain data set.