Balancing and Analyzing Player Interaction in the ESG+P Game with Machinations

Leandro Ouriques; Farmy Silva; Marcus Parreiras; Marcos Magalhães; Geraldo Xexéo

doi:10.5753/jis.2024.4186

Authors

Leandro Ouriques Federal University of Rio de Janeiro https://orcid.org/0000-0002-0043-3098
Farmy Silva Federal University of Rio de Janeiro https://orcid.org/0000-0001-7567-2504
Marcus Parreiras Federal University of Rio de Janeiro https://orcid.org/0000-0002-7225-2675
Marcos Magalhães Federal University of Rio de Janeiro https://orcid.org/0009-0009-9760-7864
Geraldo Xexéo Federal University of Rio de Janeiro https://orcid.org/0000-0003-3975-9076

DOI:

https://doi.org/10.5753/jis.2024.4186

Keywords:

Game Balancing, Game Interactivity, Player Interaction, Machinations, Game Internal Economy

Abstract

This work explores the balancing of an educational game to teach sustainable development in organizations by focusing on player interaction and employing strategies. Game success is a challenge that relies on balancing the relationships among its elements. Balancing is a complex process performed over multiple iterations, starting at game conception and continuing throughout development and testing stages. This work extends our previous case study, which did not consider player interaction for the game balancing. We built two models that contains all game mechanics using the Machinations framework. The first model includes elements that randomly produce, distribute, and consume resources, while the second model analyzes player interaction and implements four player strategies. We simulated these models in batch plays, analyzed game states, and adjusted game economies. The random model simulation achieved a victory rate of 40%, while the interactive model simulation with player strategies increased victory rates to values between 66% and 81%. These results show that player interaction and decision-making can be more decisive than randomness in achieving victory. Machinations contributed to enhancing the game, proved its usefulness for simulating complex models, and deepened our understanding of game dynamics, including player actions, potential deadlocks, and feedback mechanisms. This work supports other authors’ findings by demonstrating that balancing the game as early as possible in the development process, considering player interaction, makes the design feasible; and provides evidence that computer simulations, such as Machinations, benefit the game balance and improve the game design without the need to build a prototype and conduct extensive playtests.

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