Procedural Content Generation for Real-Time Strategy Games

Videogames are one of the most important and profitable sectors in the industry of entertainment. Nowadays, the creation of a videogame is often a large-scale endeavor and bears many similarities with, e.g., movie production. On the central tasks in the development of a videogame is content generation, namely the definition of maps, terrains, non-player characters (NPCs) and other graphical, musical and AI-related components of the game. Such generation is costly due to its complexity, the great amount of work required and the need of specialized manpower. Hence the relevance of optimizing the process and alleviating costs. In this sense, procedural content generation (PCG) comes in handy as a means of reducing costs by using algorithmic techniques to automatically generate some game contents. PCG also provides advantages in terms of player experience since the contents generated are typically not fixed but can vary in different playing sessions, and can even adapt to the player herself. For this purpose, the underlying algorithmic technique used for PCG must be also flexible and adaptable. This is the case of computational intelligence in general and evolutionary algorithms in particular. In this work we shall provide an overview of the use of evolutionary intelligence for PCG, with special emphasis on its use within the context of real-time strategy games. We shall show how these techniques can address both playability and aesthetics, as well as improving the game AI

Geração procedural de mapas em jogos de estratégia em tempo real

A geração procedural de conteúdo (PCG, do inglês Procedural Content Generation) é uma técnica bastante utilizada para a criação algorítmica de diversos conteúdos de jogo. Este trabalho analisa, a partir da revisão de literatura, a viabilidade de PCG em jogos de Estratégia em Tempo Real (RTS, do inglês Real-Time Strategy). Para isso, foram estabelecidas métricas de qualidade obtidas através de replays do jogo RTS StarCraft 2 e a partir de um algoritmo genético, foi possível gerar novos mapas para um jogo RTS.Procedural Content Generation (PCG) is a well-known data creation technique. This method uses a genetic algorithm to generate game content. This work analyses, through literature review, the viability of using PCG in Real-Time Strategy (RTS) games. For that, quality metrics were obtained by replaying StarCraft 2 matches. Using a genetic algorithm, it was possible to generate new maps for an RTS game

Using Self-Adaptive Evolutionary Algorithms to Evolve Dynamism-Oriented Maps for a Real Time Strategy Game

9th International Conference on Large Scale Scientific Computations. The final publication is available at link.springer.comThis work presents a procedural content generation system that uses an evolutionary algorithm in order to generate interesting maps for a real-time strategy game, called Planet Wars. Interestingness is here captured by the dynamism of games (i.e., the extent to which they are action-packed). We consider two different approaches to measure the dynamism of the games resulting from these generated maps, one based on fluctuations in the resources controlled by either player and another one based on their confrontations. Both approaches rely on conducting several games on the map under scrutiny using top artificial intelligence (AI) bots for the game. Statistic gathered during these games are then transferred to a fuzzy system that determines the map's level of dynamism. We use an evolutionary algorithm featuring self-adaptation of mutation parameters and variable-length chromosomes (which means maps of different sizes) to produce increasingly dynamic maps.TIN2011-28627-C04-01, P10-TIC-608

Evolving Aesthetic Maps for a Real Time Strategy Game

Artículo publicado en congreso SEED'2013 (I Spanish Symposium on Entertainment Computing), Septiembre 2013, Madrid.This paper presents a procedural content generator method that have been able to generate aesthetic maps for a real-time strategy game. The maps has been characterized based on several of their properties in order to de ne a similarity function between scenarios. This function has guided a multi-objective evolution strategy during the process of generating and evolving scenarios that are similar to other aesthetic maps while being di erent to a set of non-aesthetic scenarios. The solutions have been checked using a support-vector machine classi er and a self-organizing map obtaining successful results (generated maps have been classi ed as aesthetic maps)

A spatially-structured PCG method for content diversity in a Physics-based simulation game

This paper presents a spatially-structured evolutionary algorithm (EA) to procedurally generate game maps of di ferent levels of di ficulty to be solved, in Gravityvolve!, a physics-based simulation videogame that we have implemented and which is inspired by the n- body problem, a classical problem in the fi eld of physics and mathematics. The proposal consists of a steady-state EA whose population is partitioned into three groups according to the di ficulty of the generated content (hard, medium or easy) which can be easily adapted to handle the automatic creation of content of diverse nature in other games. In addition, we present three fitness functions, based on multiple criteria (i.e:, intersections, gravitational acceleration and simulations), that were used experimentally to conduct the search process for creating a database of maps with di ferent di ficulty in Gravityvolve!.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The riddle of togelby

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.At the 2017 Artificial and Computational Intelligence in Games meeting at Dagstuhl, Julian Togelius asked how to make spaces where every way of filling in the details yielded a good game. This study examines the possibility of enriching search spaces so that they contain very high rates of interesting objects, specifically game elements. While we do not answer the full challenge of finding good games throughout the space, this study highlights a number of potential avenues. These include naturally rich spaces, a simple technique for modifying a representation to search only rich parts of a larger search space, and representations that are highly expressive and so exhibit highly restricted and consequently enriched search spaces. We treat the creation of plausible road systems, useful graphics, highly expressive room placement for maps, generation of cavern-like maps, and combinatorial puzzle spaces.Final Accepted Versio

'Ephemerality’ in game development: opportunitiees and challenges

Ephemeral Computation (Eph-C) is a newly created computation paradigm, the purpose of which is to take advantage of the ephemeral nature (limited lifetime) of computational resources. First we speak of this new paradigm in general terms, then more specifically in terms of videogame development. We present possible applications and benefits for the main research fields associated with videogame development. This is a preliminary work which aims to investigate the possibilities of applying ephemeral computation to the products of the videogame industry. Therefore, as a preliminary work, it attempts to serve as the inspiration for other researchers or videogame developers.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Technology Solutions for Developmental Math: An Overview of Current and Emerging Practices

Reviews current practices in and strategies for incorporating innovative technology into the teaching of remedial math at the college level. Outlines challenges, emerging trends, and ways to combine technology with new concepts of instructional strategy