Procedural urban environments for FPS games

Kruse, Jan; Sosa, Ricardo; Connor, Andy M.

doi:10.1145/2843043.2843479

Cited by 6 publications

(6 citation statements)

References 11 publications

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“…Similar approaches have been adopted for terrain generation (Walsh and Gade 2010), game textures (Yoon and Kim 2012) and specific game assets (Provano et al 2015). To date there has been little focus on utilizing an IGA in the development of game maps for multiplayer FPS games, though early iterations of the research described in this paper would fall into this category (Kruse et al 2016).…”

Section: Evolving First Person Shooter Game Mapsmentioning

confidence: 99%

An Interactive Multi-Agent System for Game Design

2021

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This paper presents a novel approach to procedural generation of game maps for multi-player, competitive video games. A multi-agent evolutionary system is employed to place streets, buildings and other items, resulting in a playable video game map. The system utilises computational agents that act in conjunction with the human designer to produce maps that exhibit desirable characteristics. This paper compares the impact that the additional agents have in terms of the quality of candidate solutions. The results indicate that the use of the agents produces higher quality solutions in comparison to a traditional interactive genetic algorithm.

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Section: Evolving First Person Shooter Game Mapsmentioning

confidence: 99%

An Interactive Multi-Agent System for Game Design

2021

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“…Focusing more on the level generation focused contents, multiple works are done to either create the contents by using PCG [27], [37], [46], [38]- [45], thus automating the content generation in the game in term of its physical contents. While several other works improve such content generation into the logical contents of the game by focusing into its game difficulty [47]- [56], creating an adaptive and adjustable level generation personalized to each unique user.…”

Section: Focused Contentmentioning

confidence: 99%

A literature review of Empirical Evidence on Procedural Content Generation in Game-Related Implementation

Hafis

Tolle

Supianto

2019

JITeCS

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Procedural Content Generation (PCG) is an emerging field of study in computer science that focuses on automating the process of generating content by using algorithm, making the content generation process with less human effort. However, a more specific empirical evidence on how it is being used in a game-related implementation are still lacking. This paper presents the findings of review performed in the past 5 years looking on how PCG are being applied in game-related content, whether it is from the basic paper characteristic to analyze the trends, the field of PCG itself, and the game domain of game model and game genre. The studies had shown that PCG are being used extensively in game-related content but has seen more uses on specific type of contents rather than being used ubiquitously in all sorts of contents. The result shown that there are not specific best type of PCG method or algorithm being used instead an array of approach can be used based on what content being created. Result also shown that PCG are being used in multiple type of games, but similarly, based on the paper found, only certain types of game benefits PCG extensively such as action and platforming games while other model and genre of games have not seen much PCG application yet. Further studies are also required to analyze how experimentation and evaluation of PCG are being done as well as PCG domain in educational games as well as game-based learning, the quality catachrestic being analyzed on the papers are also worth mentioning to understand the underlying result of PCG usage in game-related contents.

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“…Offline PCG facilitate the game development process and typically involves systems that assist game developers in their design process [16,17] or through the creation of game assets [18] or levels [19][20][21]. Traditional approaches to PCG utilise a number of techniques or theoretical frameworks, such as L-systems [22] or other space based approaches 3 [23], statecharts [24] and petri nets [25], along with an emergence of declarative approaches [26] or those using techniques such as answer set programming [27].…”

Section: Procedural Content Generationmentioning

confidence: 99%

Evolutionary generation of game levels

Connor¹,

Greig²,

Kruse³

2018

EAI Endorsed Transactions on Creative Technologies

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This paper outlines an approach for evolutionary procedural generation of video game content. The study deals with the automatic generation of game level designs using genetic algorithms and the development of a fitness function that describes the playability of the game level. The research explores whether genetic algorithms have the ability to produce outcomes that demonstrate characteristics that arise through human creativity, and whether these automated approaches offer any benefits in terms of time and effort involved in the design process. The approach is compared to a random method and the results show that the genetic algorithm is more consistent in finding levels; however analysis of the game levels indicates that the fitness function is not fully capturing level playability. The ability to produce playable levels decreases as the play area increases, however there is potential to produce larger maps that are both playable and arguably creative through a recombination method.

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Procedural urban environments for FPS games

Cited by 6 publications

References 11 publications

An Interactive Multi-Agent System for Game Design

An Interactive Multi-Agent System for Game Design

A literature review of Empirical Evidence on Procedural Content Generation in Game-Related Implementation

Evolutionary generation of game levels

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