Enhancing Level Difficulty and Additional Content in Platform Videogames through Graph Analysis

Proceedings of the 11th Conference on Advances in Computer Entertainment Technology

2014

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In this paper we extend the existing metrics for estimating difficulty, directed to action games (in particular, platform videogames) and taking into account different types of challenges. Specifically, we analyse how challenges are represented in time and space and observe the players' behaviour when facing such challenges. Accordingly, we propose a set of models to predict the probability of failure and success in different situations. This type of assessment can serve as a validation mechanism for automatic level generation algorithms and also to perform adaptive difficulty techniques. As a final point, we analyse multiple gameplay information retrieved from gaming sessions, in which 40 users performed over 10000 trials in different types of challenges. We have verified that the main hypotheses behind the proposed metrics are applicable and the estimators are valid approximations to the players' behaviour.

Section: The Notion Of Difficultymentioning

confidence: 99%

Difficulty in action based challenges

Proceedings of the 11th Conference on Advances in Computer Entertainment Technology

2014

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“…To achieve a more detailed evaluation one needs a more complex alternative. In a previous work [9], we proposed a framework to measure difficulty based on level structure and gap features, which can be an alternative for this purpose. The main issue that this may cause is an increase of complexity for the fitness function, which will result in higher computation times to produce one valid level.…”

Section: Fitness Functionmentioning

confidence: 99%

Automatic level generation for platform videogames using genetic algorithms

Proceedings of the 8th International Conference on Advances in Computer Entertainment Technology

2011

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In this document we present an investigation on automatically generating levels for platform videogames. Common approaches for this problem are rhythm based, where input patterns are transformed in a valid geometry, and chunk based, where samples are humanly created and automatically assembled like a puzzle. The proposal hereby presented is to explore this challenge with the usage of Genetic Algorithms, facing it as a search problem, in order to achieve higher expressivity and less linearity than in rhythm based approach and without requiring human creation as it happens with the chunk based approach. With simple heuristics the system is able to generate playable levels in a small amount of time (one level is created in less than a minute) and with considerable diversity, as our results show.

“…It consists in the integration of a set of simple design patterns to make the algorithm evolve to a set of valid game geometries with different features. To improve content inside those levels, we have also proposed a level adaptation algorithm [17] that is able to fill the main geometry with additional gaming entities, such as enemies or traps. Lastly, an integrated system where those concepts are applied was also implemented [18].…”

Section: Procedural Content Generation (Pcg) In Platform Videogamesmentioning

confidence: 99%

The Challenge of Automatic Level Generation for Platform Videogames Based on Stories and Quests

Lecture Notes in Computer Science

2013

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Abstract. In this article we bring the concepts of narrativism and ludology to automatic level generation for platform videogames. The initial motivation is to understand how this genre has been used as a storytelling medium. Based on a narrative theory of games, the differences among several titles have been identified. In addition, we propose a set of abstraction layers to describe the content of a quest-based story in the particular context of videogames. Regarding automatic level generation for platform videogames, we observed that the existing approaches are directed to lower abstraction concepts such as avatar movements without a particular context or meaning. This leads us to the challenge of automatically creating more contextualized levels rather than only a set of consistent and playable entertaining tasks. With that in mind, a set of higher level design patterns are presented and their potential usages are envisioned and discussed. IntroductionThe way how narratives and videogames are connected is still a topic that is open to debate. Nevertheless, it is undeniable that over the years several videogames have been used to tell stories. In fact, this topic started to catch attention in later years with the appearance of textual adventure videogames, some kind of Interactive Fiction [1]. The term ludology has been proposed by Frasca [2] as a movement based on narratology having different features with distinct merits. Therefore, the main question is not if games are effectively narratives or not but how they relate to narratives. An interesting recent approach on this question is a model presented by Aarseth [3]. Briefly, the author confirms videogames as an interactive fiction medium, whose elements can be characterized in a ludo-narrative dimension. The different elements can have a more meaningful (narrative) effect or a more challenging and amusing (ludic) importance. In the context of automatic level generation, existing algorithms focus the lower abstraction concepts to provide adequate actions (Section 2), yet higher abstraction concepts must be considered to create more intricate scenarios. We present our studies in how to relate stories and story related concepts with automatic level generation to produce more meaningful content, which include: the definition of a set of abstraction layers in hero-centred stories (Section 3.1); a study on the platformers' storytelling capabilities (Section 3.2); the definition of higher level game design patterns for platformers