30,136 research outputs found
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
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
Modern Trends in the Automatic Generation of Content for Video Games
Attractive and realistic content has always played a crucial
role in the penetration and popularity of digital games, virtual
environments, and other multimedia applications. Procedural content
generation enables the automatization of production of any type of game
content including not only landscapes and narratives but also game
mechanics and generation of whole games. The article offers a
comparative analysis of the approaches to automatic generation of
content for video games proposed in last five years. It suggests a new
typology of the use of procedurally generated game content comprising of
categories structured in three groups: content nature, generation process,
and game dependence. Together with two other taxonomies – one of
content type and the other of methods for content generation – this
typology is used for comparing and discussing some specific approaches to
procedural content generation in three promising research directions
based on applying personalization and adaptation, descriptive languages,
and semantic specifications
Developing serious games for cultural heritage: a state-of-the-art review
Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented
Generating Levels That Teach Mechanics
The automatic generation of game tutorials is a challenging AI problem. While
it is possible to generate annotations and instructions that explain to the
player how the game is played, this paper focuses on generating a gameplay
experience that introduces the player to a game mechanic. It evolves small
levels for the Mario AI Framework that can only be beaten by an agent that
knows how to perform specific actions in the game. It uses variations of a
perfect A* agent that are limited in various ways, such as not being able to
jump high or see enemies, to test how failing to do certain actions can stop
the player from beating the level.Comment: 8 pages, 7 figures, PCG Workshop at FDG 2018, 9th International
Workshop on Procedural Content Generation (PCG2018
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
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