An integrated process for game balancing

Beyer, Marlene; Agureikin, Aleksandr; Laenger, Christoph; Nolte, Felix; Winterberg, Jonas; Renka, Marcel; Rieger, Martin; Pflanzl, Nicolas; Preuß, Mike; Volz, Vanessa

doi:10.1109/cig.2016.7860425

Cited by 19 publications

(10 citation statements)

References 10 publications

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“…The work [28] on describing an integrated game balancing process gives a better understanding of the problems of automating the balancing process, and illustrates ways to use such algorithms to solve game development problems. Among the conclusions of this paper is that artificial intelligence often does not play as a human would play.…”

Section: The Problem Of Balancing Game Valuesmentioning

confidence: 99%

“…Our development for automated balancing of game parameters on a prototype game model [28] has shown that Machinations balance diagrams can be used not only for manual balancing of game parameters, but also for automated balancing of game parameters, thus reducing the time spent on this lengthy process. However, although the Machination project (see Fig.…”

Section: The Problem Of Balancing Game Valuesmentioning

confidence: 99%

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Branched Structure Component for a Video Game Scenario Prototype Generator

Sahibgareeva

Kugurakova

2021

Scientific Conference “Scientific Services &Amp; Internet”

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The task of automating the routine work of computer game writers, narrative designers, set forth in earlier works, has been continued in the presented work. The issues of visualization of branching narrative structures of computer games are considered, the analysis of various approaches to visualization of the plot and other important components of a video game, such as, for example, automatic balancing of quantitative parameters, is carried out. The paper presents the chosen technological stack and gives specific solutions for storage in the form of a structured scenario, allowing the generation of continuing story branches and testing the narrative prototyping stage using the automatically generated text novel.

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Section: The Problem Of Balancing Game Valuesmentioning

confidence: 99%

Section: The Problem Of Balancing Game Valuesmentioning

confidence: 99%

Branched Structure Component for a Video Game Scenario Prototype Generator

Sahibgareeva

Kugurakova

2021

Scientific Conference “Scientific Services &Amp; Internet”

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“…Quantitative methods for understanding games have been proposed in many forms. [17] presents a similar balancing overview to ours, introducing a generic iterative an automated balancing process. of sampling game parameters, using AI players (or real humans) and testing if a desirable balancing has been achieved.…”

Section: Related Workmentioning

confidence: 99%

Metagame Autobalancing for Competitive Multiplayer Games

Hernández

Gbadamosi

Goodman

et al. 2020

2020 IEEE Conference on Games (CoG)

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Automated game balancing has often focused on single-agent scenarios. In this paper we present a tool for balancing multi-player games during game design. Our approach requires a designer to construct an intuitive graphical representation of their meta-game target, representing the relative scores that high-level strategies (or decks, or character types) should experience. This permits more sophisticated balance targets to be defined beyond a simple requirement of equal win chances. We then find a parameterization of the game that meets this target using simulation-based optimization to minimize the distance to the target graph. We show the capabilities of this tool on examples inheriting from Rock-Paper-Scissors, and on a more complex asymmetric fighting game.

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“…What constitutes a balanced game is varies widely because the term depends on the game genre. Beyer et al [1] describe game balancing as:…”

Section: Introductionmentioning

confidence: 99%

“…Approaches to aid competitive game balancing without using player data include using genetic algorithms [5] and artificial agents [1] to automate game play. However, these approaches do not consider strategies that develop in response to repeated plays of a game.…”

Section: Introductionmentioning

confidence: 99%

Balancing Turn-Based Games With Chained Strategy Generation

et al. 2021

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Probabilistic model checking can overcome much of the complexity inherent in balancing games. Game balancing is the careful maintenance of relationships between the ways in which a game can be played, to ensure no single way is strictly better than all others and that players are offered a wide variety of ways to play successfully. We introduce a novel approach towards automating game balancing using probabilistic model checking called chained strategy generation (CSG). This involves generating chains of adversarial strategies which mimic the way players adapt their approach during repeated plays of a game. We use CSG to map out the evolving metagame. The trends identified can allow game developers to identify strategies which will be too strong and ways of playing the game which a player may want to use, but are never viable for successful competitive play. We introduce a case study, a game called RPGLite, and use CSG to compare five candidate configurations for the game. We show how to determine which configurations of RPGLite lead to a more fair and interesting experience for players. We also identify unexpected trends in how the strategies evolve. Our approach introduces a new technique for improving game development and player experience.

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An integrated process for game balancing

Cited by 19 publications

References 10 publications

Branched Structure Component for a Video Game Scenario Prototype Generator

Branched Structure Component for a Video Game Scenario Prototype Generator

Metagame Autobalancing for Competitive Multiplayer Games

Balancing Turn-Based Games With Chained Strategy Generation

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