21,752 research outputs found
Maximising gain for minimal pain: Utilising natural game mechanics
This paper considers the application of natural games mechanics within higher education as a vehicle to encourage student engagement and achievement of desired learning outcomes. It concludes with desiderata of features for a learning environment when used for assessment and a reflection on the gap between current and aspired learning provision. The context considered is higher (tertiary) education, where the aims are both to improve studentsâ engagement with course content and also to bring about potential changes in the studentsâ learning behaviour. Whilst traditional approaches to teaching and learning may focus on dealing with large classes, where the onus is frequently on efficiency and on the effectiveness of feedback in improving understanding and future performance, intelligent systems can provide technology to enable alternative methods that can cope with large classes that preserve the cost-benefits. However, such intelligent systems may also offer improved learning outcomes via a personalised learning experience. This paper looks to exploit particular properties which emerge from the game playing process and seek to engage them in a wider educational context. In particular we aim to use game engagement and Flow as natural dynamics that can be exploited in the learning experience
General general game AI
Arguably the grand goal of artificial intelligence
research is to produce machines with general intelligence: the
capacity to solve multiple problems, not just one. Artificial
intelligence (AI) has investigated the general intelligence capacity
of machines within the domain of games more than any other
domain given the ideal properties of games for that purpose:
controlled yet interesting and computationally hard problems.
This line of research, however, has so far focused solely on
one specific way of which intelligence can be applied to games:
playing them. In this paper, we build on the general game-playing
paradigm and expand it to cater for all core AI tasks within a
game design process. That includes general player experience
and behavior modeling, general non-player character behavior,
general AI-assisted tools, general level generation and complete
game generation. The new scope for general general game AI
beyond game-playing broadens the applicability and capacity of
AI algorithms and our understanding of intelligence as tested
in a creative domain that interweaves problem solving, art, and
engineering.peer-reviewe
The Industry and Policy Context for Digital Games for Empowerment and Inclusion:Market Analysis, Future Prospects and Key Challenges in Videogames, Serious Games and Gamification
The effective use of digital games for empowerment and social inclusion (DGEI) of people and communities at risk of exclusion will be shaped by, and may influence the development of a range of sectors that supply products, services, technology and research. The principal industries that would appear to be implicated are the 'videogames' industry, and an emerging 'serious games' industry. The videogames industry is an ecosystem of developers, publishers and other service providers drawn from the interactive media, software and broader ICT industry that services the mainstream leisure market in games, The 'serious games' industry is a rather fragmented and growing network of firms, users, research and policy makers from a variety of sectors. This emerging industry is are trying to develop knowledge, products, services and a market for the use of digital games, and products inspired by digital games, for a range of non-leisure applications. This report provides a summary of the state of play of these industries, their trajectories and the challenges they face. It also analyses the contribution they could make to exploiting digital games for empowerment and social inclusion. Finally, it explores existing policy towards activities in these industries and markets, and draws conclusions as to the future policy relevance of engaging with them to support innovation and uptake of effective digital game-based approaches to empowerment and social inclusion.JRC.J.3-Information Societ
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
A scheme for creating digital entertainment with substance
Computer games constitute a major branch of the
entertainment industry nowadays. The financial
and research potentials of making games more appealing (or else more interesting) are more than impressive. Interactive and cooperative characters can
generate more realism in games and satisfaction for
the player. Moreover, on-line (while play) machine
learning techniques are able to produce characters
with intelligent capabilities useful to any gameâs
context. On that basis, richer human-machine interaction through real-time entertainment, player
and emotional modeling may provide means for
effective adjustment of the non-player charactersâ
behavior in order to obtain games of substantial
entertainment. This paper introduces a research
scheme for creating NPCs that generate entertaining games which is based interdisciplinary on the
aforementioned areas of research and is foundationally supported by several pilot studies on testbed games. Previous work and recent results are
presented within this framework.peer-reviewe
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