On Modeling, Evaluating and Increasing Players’ Satisfaction Quantitatively: Steps towards a Taxonomy

Nogueira, M. A.; Cotta, Carlos; Fernández-Leiva, Antonio J.

doi:10.1007/978-3-642-29178-4_25

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…This high satisfaction can be achieved via the automated adaptation of the game in response to the player's needs [7] using computational intelligence (CI) techniques. Traditionally, CI has been applied to generate strategies that define the behaviour of the non-player characters (NPC), but it can be also applied to many other aspects of game development such as computational narratives, player modelling, learning in games, intelligent camera control, and procedure content generation (PCG), among other -see [6].…”

Section: Introductionmentioning

confidence: 99%

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

Lara-Cabrera

Cotta

Fernández-Leiva

2014

Large-Scale Scientific Computing

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Abstract. This 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.

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Section: Introductionmentioning

confidence: 99%

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

Lara-Cabrera

Cotta

Fernández-Leiva

2014

Large-Scale Scientific Computing

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“…However, the generated maps lacked aesthetics (for example, maps with all their planets clustered in a small region, see Figure 2), which is an interesting feature apart from the fun that may lead to increase the player satisfaction. It turns out that fun and aesthetics are two complementary ways of achieving the same goal [27]. Moreover, non-aesthetic maps may confuse the player, reducing his/her satisfaction or even leading him/her to stop playing the game.…”

Section: B Introducing Aestheticsmentioning

confidence: 99%

Procedural Content Generation for Real-Time Strategy Games

Lara-Cabrera¹,

Nogueira-Collazo²,

Cotta³

et al. 2015

IJIMAI

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-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 realtime strategy games. We shall show how these techniques can address both playability and aesthetics, as well as improving the game AI.

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On balance and dynamism in procedural content generation with self-adaptive evolutionary algorithms

2014

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On Modeling, Evaluating and Increasing Players’ Satisfaction Quantitatively: Steps towards a Taxonomy

Cited by 5 publications

References 14 publications

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

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

Procedural Content Generation for Real-Time Strategy Games

On balance and dynamism in procedural content generation with self-adaptive evolutionary algorithms

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