Working Paper Class 30
Video games are complex interactive systems that involve multiple agents, such as human players, artificial intelligence (AI) agents, and game developers, who interact strategically in various scenarios and environments. Designing video games that are engaging, immersive, and fair requires understanding the behavior and preferences of these agents, as well as the trade-offs and incentives that arise from the game rules and mechanisms. In this paper, we extend the theory of simplicity in games and mechanism design to the domain of video games. We introduce a general class of simplicity standards that vary the cognitive abilities required of agents in video games, such as memory, attention, anticipation, and learning. We use these standards to provide characterizations of simple mechanisms in video game environments with and without transfers, such as scoring systems, reward structures, difficulty levels, and matchmaking algorithms. We also study the implications of simplicity for the design of dynamic mechanisms in video games, such as auctions, markets, and voting systems. We illustrate our results with examples from popular video games, such as the Fortnite, Metroid Prime, Minecraft, Among Us, FIFA, NBA 2K, and MarioKart series. We show how simplicity can enhance the gameplay experience and create more realistic and adaptive AI agents. We also discuss the limitations and challenges of simplicity in video games, such as ethical issues, computational complexity, and human factors.
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Opoku-Agyemang, Kweku A. (2023). "Simplicity in Video Games: Theory and Applications." Machine Learning X Doing Working Paper Class 30. Machine Learning X Doing.
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