A Short Introduction to Procedural Content Generation Algorithms for Videogames

Barriga, Nicolas A.

doi:10.1142/s0218213019300011

Cited by 26 publications

(14 citation statements)

References 9 publications

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“…Content creation is one of the main costs of developing a video game, it is estimated to be around 30%-40% of the US 20M−150M average budget for AAA games [Bar19]. To agile the content creation process, procedural content generation is an alternative to manual design of the game assets, providing techniques to automate the content generation [Hen13].…”

Section: Literature Reviewmentioning

confidence: 99%

Influence of the underwater environment in the procedural generation of marine alga Asparagopsis Armata

Rodrigues¹,

Sousa²,

Rodrigues³

et al. 2022

CSRN

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Content generation is a heavy task in virtual worlds design. Procedural content generation techniques aim to agile this process by automating the 3D modelling with some degree of parametrisation. The novelty of this work is the procedural generation of the marine alga (Asparagopsis armata), taking into consideration the underwater environmental factors. The depth and the occlusion were the two parameters in this study to simulate how the alga growth is influenced by the environment where the alga grows. Starting by building a prototype to explore different L-systems categories to model the alga, the stochastic L-systems with parametric features were selected to generate different alga plasticities. Qualitative methods were used to evaluate the designed grammar and alga’s animation results by comparing videos and images of the Asparagopsis armata with the computer-generated versions.

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Section: Literature Reviewmentioning

confidence: 99%

Influence of the underwater environment in the procedural generation of marine alga Asparagopsis Armata

Rodrigues¹,

Sousa²,

Rodrigues³

et al. 2022

CSRN

View full text Add to dashboard Cite

show abstract

“…Algorithm Characteristics [47] Fractal noise, e.g., Perlin noise Interpolation discontinuity of the second-order and nonoptimal gradient calculation [48] Midpoint displacement algorithm The midpoint-displacement model for mountains now includes a squig-curve model of a river's path [49] Diamond-square algorithm Terrain height is generated at random from four seed values organized in a grid of points, covering the entire plane in squares [50] Simple collision algorithm Texturing and creating lifelike textures [51] Squarified treemap algorithm In a two-dimensional region, show tree structures [52] Intent-driven partial-order causal link (IPOCL) planning algorithm It solves the constraints of traditional causal dependency planners [53] Long short-term memory (LSTM) Generation of simulated and original game levels and human level trajectories [54] Multidimensional Markov chains The state space of a Markov chain that simulates the behavior of a system is frequently infinite in several dimensions [53] Autoencoder CNN algorithm Heuristic approach for generation of terrains of all kinds Journal of Sensors that can generate terrains for various purposes in other target applications.…”

Section: Referencementioning

confidence: 99%

A Critical Evaluation of Procedural Content Generation Approaches for Digital Twins

et al. 2022

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Procedural content generation (PCG) of terrains is one of the main building blocks for creating an automated and real-time virtual world. This study provides and in-depth review of the different tools, algorithms, and engines used for the PCG of terrains for the PCG of digital worlds; we focus especially on terrain generation but address also the main issues related to build structures and characters. It is important to know that the PCG of terrains can be implemented in a multidisciplinary scenario, for instance, modeling of games, simulating industrial maps, urban and rural planning of developments, government, and nongovernmental agency improvement plans. Many problems in current approaches were identified from the literature, where most of the researches studied were merely throwaway prototyping based, i.e., proof of concept-based systems, and were not tested in the real environment. Also, genetic algorithm-based PCG of terrains lack multiple features such as roads and buildings. The virtual cities generated through different engines were lacking a realistic look and feel. Terrain generation through multiobjective evolutionary algorithms (MOEAs) is investigated, and it is deemed the usage was restricted to the gaming domain and not extended to other fields. Findings suggest that the correctness of generated terrain is a big issue in the automatic generation of terrains. Thus, a focus on the automated correctness check is required. Other important content generation in video games such as structure generation and character generation has been extensively studied, and the techniques are analysed in the further sections of this research work.

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“…There are many methods for developing game content. These are constructive, searched based, and machine learning-based techniques [ 30 ]. Constructive techniques are fast and effective but are not suitable for complex contents.…”

Section: Related Workmentioning

confidence: 99%

BiLSTM and dynamic fuzzy AHP-GA method for procedural game level generation

İnce

2021

Neural Comput & Applic

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The use of games in daily life, especially in education, has been in an incline during the COVID-2019 pandemic. Thus, game-based learning environments have caused an increase in the need of game contents, but generation of the game contents and levels is a time-consuming and costly process. Generated game contents and levels should be balanced, dense, aesthetic and reachable. Also, the time as well as the costs spent should be decreased. In order to overcome this problem, automatic and intelligent game content and level generation methods have emerged, and procedural content generation (PCG) is the most popular one of these methods. Artificial intelligence techniques are used for procedural game level generation instead of traditional methods. In this study, bidirectional long short-term memory (BiLSTM) and fuzzy analytic hierarchy process-genetic algorithm (FAHP-GA) methods were used to generate procedural game levels. This proposed hybrid system was used in a developed educational game as a case study to create game levels. The performance of the proposed study was compared to the other multi-criteria decision-making (MCDM) methods, and also further statistical analyses were investigated. The results showed that the BiLSTM-based FAHP-GA method can be used for procedural game level generation effectively.

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A Short Introduction to Procedural Content Generation Algorithms for Videogames

Cited by 26 publications

References 9 publications

Influence of the underwater environment in the procedural generation of marine alga Asparagopsis Armata

Influence of the underwater environment in the procedural generation of marine alga Asparagopsis Armata

A Critical Evaluation of Procedural Content Generation Approaches for Digital Twins

BiLSTM and dynamic fuzzy AHP-GA method for procedural game level generation

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