Wargames as Data: Addressing the Wargamer's Trilemma
Policymakers often want the very best data with which to make decisions--particularly when concerned with questions of national and international security. But what happens when this data is not available? In those instances, analysts have come to rely on synthetic data-generating processes--turning to modeling and simulation tools and survey experiments among other methods. In the cyber domain, where empirical data at the strategic level are limited, this is no different--cyber wargames are quickly becoming a principal method for both exploring and analyzing the security challenges posed by state and non-state actors in cyberspace. In this chapter, we examine the design decisions associated with this method.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Open-Ended Wargames with Large Language Models
Wargames are a powerful tool for understanding and rehearsing real-world decision making. Automated play of wargames using artificial intelligence (AI) enables possibilities beyond those of human-conducted games, such as…
Decision MakingShall We Play a Game? Language Models for Open-ended Wargames
Wargames are simulations of conflicts in which participants' decisions influence future events. While casual wargaming can be used for entertainment or socialization, serious wargaming is used by experts to explore strat…
Quantifying the Blockchain Trilemma: A Comparative Analysis of Algorand, Ethereum 2.0, and Beyond
Blockchain technology is essential for the digital economy and metaverse, supporting applications from decentralized finance to virtual assets. However, its potential is constrained by the "Blockchain Trilemma," which ne…
POSPlaying Hex and Counter Wargames using Reinforcement Learning and Recurrent Neural Networks
Hex and Counter Wargames are adversarial two-player simulations of real military conflicts requiring complex strategic decision-making. Unlike classical board games, these games feature intricate terrain/unit interaction…
Board GamesDecision MakingBeyond the Generative Learning Trilemma: Generative Model Assessment in Data Scarcity Domains
Data scarcity remains a critical bottleneck impeding technological advancements across various domains, including but not limited to medicine and precision agriculture. To address this challenge, we explore the potential…