An Integrated Framework for AI Assisted Level Design in 2D Platformers

The design of video game levels is a complex and critical task. Levels need to elicit fun and challenge while avoiding frustration at all costs. In this paper, we present a framework to assist designers in the creation of levels for 2D platformers. Our framework provides designers with a toolbox (i) to create 2D platformer levels, (ii) to estimate the difficulty and probability of success of single jump actions (the main mechanics of platformer games), and (iii) a set of metrics to evaluate the difficulty and probability of completion of entire levels. At the end, we present the results of a set of experiments we carried out with human players to validate the metrics included in our framework.Comment: Submitted to the IEEE Game Entertainment and Media Conference 201

Gaming capital: Rethinking literacy

This paper is part of the symposium: Gameplay, gameplayers and gaming capital: Exploring intersections between games, education and adolescent subjectivities in virtual worlds PEER REFEREEING REQUIRED In rethinking literacy education in light of unprecedented technological change, this paper reports on adolescent gamers and their accumulation of gaming capital. This is in opposition to more pervasive assumptions about gaming as mindless entertainment, learning simulations, ideological tools and interactive mediums for the masses. We see the need to research the medium of games in their entirety, exploring their uniqueness as a medium--while at the same time--making connections to a wider media ecology (Fuller, 2005) that includes more than the games themselves. This media ecology of videogames is demonstrated in part by the 'paratextual' (Consalvo, 2007) industries that support game play, production and design. The 'paratext' is central to gaming capital in creating individual and group systems of distinction within gaming culture. Because we understand videogames as actions across social fields enacted through the actions of players or 'operators' on software, we also deem it necessary to understand both the operator and machines' diegetic and non-diegetic actions (Galloway, 2006). This distinction allows us to think about games as more than texts, literacy practices and narratives, which highlights games' significance in technoclture as systems (Salen, 2008), procedures (Bogost, 2007), algorithms (Galloway, 2006; Wark, 2007), configurations and code (Lessig, 1999; Manovich, 2001). In conclusion we provide a series of interview questions developed to uncover adolescents' gaming capital. We also propose a heuristic to map a players' total volume of gaming capital to better understand how gaming capital establishes trajectories of exchange between cultural and economic capitals and its implications for literacy education

Automated Game Design Learning

While general game playing is an active field of research, the learning of game design has tended to be either a secondary goal of such research or it has been solely the domain of humans. We propose a field of research, Automated Game Design Learning (AGDL), with the direct purpose of learning game designs directly through interaction with games in the mode that most people experience games: via play. We detail existing work that touches the edges of this field, describe current successful projects in AGDL and the theoretical foundations that enable them, point to promising applications enabled by AGDL, and discuss next steps for this exciting area of study. The key moves of AGDL are to use game programs as the ultimate source of truth about their own design, and to make these design properties available to other systems and avenues of inquiry.Comment: 8 pages, 2 figures. Accepted for CIG 201

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

AI Researchers, Video Games Are Your Friends!

If you are an artificial intelligence researcher, you should look to video games as ideal testbeds for the work you do. If you are a video game developer, you should look to AI for the technology that makes completely new types of games possible. This chapter lays out the case for both of these propositions. It asks the question "what can video games do for AI", and discusses how in particular general video game playing is the ideal testbed for artificial general intelligence research. It then asks the question "what can AI do for video games", and lays out a vision for what video games might look like if we had significantly more advanced AI at our disposal. The chapter is based on my keynote at IJCCI 2015, and is written in an attempt to be accessible to a broad audience.Comment: in Studies in Computational Intelligence Studies in Computational Intelligence, Volume 669 2017. Springe

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