Data-driven design : a case for maximalist game design

Maximalism in art refers to drawing on and combining multiple different sources for art creation, embracing the resulting collisions and heterogeneity. This paper discusses the use of maximalism in game design and particularly in data games, which are games that are generated partly based on open data. Using Data Adventures, a series of generators that create adventure games from data sources such as Wikipedia and Open- StreetMap, as a lens we explore several tradeoffs and issues in maximalist game design. This includes the tension between transformation and fidelity, between decorative and functional content, and legal and ethical issues resulting from this type of generativity. This paper sketches out the design space of maximalist data-driven games, a design space that is mostly unexplored.peer-reviewe

Data-driven Design: A Case for Maximalist Game Design

Maximalism in art refers to drawing on and combining multiple different sources for art creation, embracing the resulting collisions and heterogeneity. This paper discusses the use of maximalism in game design and particularly in data games, which are games that are generated partly based on open data. Using Data Adventures, a series of generators that create adventure games from data sources such as Wikipedia and OpenStreetMap, as a lens we explore several tradeoffs and issues in maximalist game design. This includes the tension between transformation and fidelity, between decorative and functional content, and legal and ethical issues resulting from this type of generativity. This paper sketches out the design space of maximalist data-driven games, a design space that is mostly unexplored.Comment: 9 pages, 2 Figures, Accepted in ICCC 201

A holistic approach for semantic-based game generation

The Web contains vast sources of content that could be reused to reduce the development time and effort to create games. However, most Web content is unstructured and lacks meaning for machines to be able to process and infer new knowledge. The Web of Data is a term used to describe a trend for publishing and interlinking previously disconnected datasets on the Web in order to make them more valuable and useful as a whole. In this paper, we describe an innovative approach that exploits Semantic Web technologies to automatically generate games by reusing Web content. Existing work on automatic game content generation through algorithmic means focuses primarily on a set of parameters within constrained game design spaces such as terrains or game levels, but does not harness the potential of already existing content on the Web for game generation. We instead propose a holistic and more generally-applicable game generation solution that would identify suitable Web information sources and enrich game content with semantic meta-structures.The research work disclosed in this publication is partially funded by the REACH HIGH Scholars Programme — Post- Doctoral Grants. The grant is part-financed by the European Union, Operational Programme II — Cohesion Policy 2014- 2020 Investing in human capital to create more opportunities and promote the wellbeing of society — European Social Fund.peer-reviewe

Generative Design in Minecraft (GDMC), Settlement Generation Competition

This paper introduces the settlement generation competition for Minecraft, the first part of the Generative Design in Minecraft challenge. The settlement generation competition is about creating Artificial Intelligence (AI) agents that can produce functional, aesthetically appealing and believable settlements adapted to a given Minecraft map - ideally at a level that can compete with human created designs. The aim of the competition is to advance procedural content generation for games, especially in overcoming the challenges of adaptive and holistic PCG. The paper introduces the technical details of the challenge, but mostly focuses on what challenges this competition provides and why they are scientifically relevant.Comment: 10 pages, 5 figures, Part of the Foundations of Digital Games 2018 proceedings, as part of the workshop on Procedural Content Generatio

Automatic level generation for platform videogames using genetic algorithms

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

Automated iterative game design

Computational systems to model aspects of iterative game design were proposed, encompassing: game generation, sampling behaviors in a game, analyzing game behaviors for patterns, and iteratively altering a game design. Explicit models of the actions in games as planning operators allowed an intelligent system to reason about how actions and action sequences affect gameplay and to create new mechanics. Metrics to analyze differences in player strategies were presented and were able to identify flaws in game designs. An intelligent system learned design knowledge about gameplay and was able to reduce the number of design iterations needed during playtesting a game to achieve a design goal. Implications for how intelligent systems augment and automate human game design practices are discussed.Ph.D

AI-based game design patterns

This paper proposes a model for designing games around Artificial Intelligence (AI). AI-based games put AI in the foreground of the player experience rather than in a supporting role as is often the case in many commercial games. We analyze the use of AI in a number of existing games and identify design patterns for AI in games. We propose a generative ideation technique to combine a design pattern with an AI technique or capacity to make new AI-based games. Finally, we demonstrate this technique through two examples of AI-based game prototypes created using these patterns

Framing tension for game generation

Emotional progression in narratives is carefully structured by human authors to create unexpected and exciting situations, often culminating in a climactic moment. This paper explores how an autonomous computational designer can create frames of tension which guide the procedural creation of levels and their soundscapes in a digital horror game. Using narrative concepts, the autonomous designer can describe an intended experience that the automated level generator must adhere to. The level generator interprets this intent, bound by the possibilities and constraints of the game. The tension of the generated level guides the allocation of sounds in the level, using a crowdsourced model of tension.peer-reviewe

Boosting computational creativity with human interaction in mixed-initiative co-creation tasks

Research in computational creativity often focuses on autonomously creative systems, which incorporate creative processes and result in creative outcomes. However, the integration of artificially intelligent processes in human-computer interaction tools necessitates that we identify how computational creativity can be shaped and ultimately enhanced by human intervention. This paper attempts to connect mixed-initiative design with established theories of computational creativity, and adapt the latter to accommodate a human initiative impacting computationally creative processes and outcomes. Several case studies of mixed-initiative tools for design and play are used to corroborate the arguments in this paper.peer-reviewe