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Dagstuhl Seminar 17471

Artificial and Computational Intelligence in Games: AI-Driven Game Design

( Nov 19 – Nov 24, 2017 )
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Motivation
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With the dramatic growth of the game industry over the past decade, its rapid pervasion in many sectors of today's society, and the increased complexity of games, game development has reached a point where it is no longer humanly possible to use only manual techniques to create games. Large parts of games need to be designed, built, and tested automatically. In recent years, researchers have delved into artificial intelligence techniques to support, assist, and even drive game development. Such techniques include procedural content generation, automated narration, player modelling and adaptation, and automated game design. This research is still very young, but already the games industry is taking small steps to integrate some of these techniques in their approach to design.

The goal of the proposed seminar is to bring together researchers and industry representatives who work at the forefront of artificial intelligence (AI) and computational intelligence (CI) in games, to (1) explore and extend the possibilities of AI-driven game design, (2) to identify the most viable applications of AI-driven game design in the game industry, and (3) to investigate new approaches to AI-driven game design. To this end, the seminar will include a wide range of researchers and developers, including specialists in AI/CI for abstract games, commercial video games, and serious games.

The expected outcome of the seminar is a better understanding of a unified vision on AI-driven game design, using input from both scientists as well as AI specialists from industry. This may have a significant impact both on the science of creative algorithms, as well as on the economic and technological aspects of commercial game development.

Copyright Elisabeth André, Michael Mateas, Mike Preuß, and Pieter Spronck
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The video game industry has been developing rapidly in the past decade. Whereas ten years ago video games were almost exclusively aimed at entertainment, nowadays they are used in a variety of places in everyday life. All kinds of organizations now use video games for simulation and training. Educational institutes use video games to enrich and replace parts of courses. Governmental and health care agencies use video games to educate people and stimulate them to lead more productive lives. On top of that, the entertainment-focused games industry continues to grow and is a major industry both culturally and financially.

Two parallel developments can be observed in the games industry. On the one hand, the high-profile entertainment games ("triple-A games") see a steady increase of time and financial resources invested in their development, to keep up with technological advances and to be able to compete in a tough market. On the other hand, the number of smaller, special-purpose games in development (including so-called "serious games") increases dramatically too, in particular in research, training, and education. Moreover, as the pervasiveness of video games increases, so does the the number of people involved in creating them. The job of creating games is no longer limited to specialist programmers and artists. Instead, those who need to use the games become heavily involved in their creation.

The serious-games domain poses additional challenges to game development beyond all the challenges already posed by games for entertainment, namely the need for a strong relation with the "real world". Serious games often have a purpose in training, which entails that the game worlds must be a realistic depiction of the actual environment in which user functions, in particular where "behaviors" are concerned. The big data revolution means that huge quantities of data about the real world are becoming available along with the means of processing them, which may offer the possibility to automatically construct games on the basis of such data. This is a particularly enticing notion, given the financial constraints for constructing serious games, which means that professional content producers might not be available.

Furthermore, new computer games are expected to much better incorporate the different needs of a wide variety of customers, to provide more alternative modes, solution paths, incentives, emotional states, and difficulty levels. Game design, and especially balancing, must take this into account. However, this increases the complexity of design and production considerably, such that AI-based tools that can assist the human developer or even partly automatize processes are more desired than ever.

Summarizing, we note the following four trends in modern game development:

  1. Technological advances have lead to an increased challenge in developing modern video games, even for expert game developers
  2. There is an increased need for non-experts to be able to design and develop games
  3. There is an increased need for realism in the virtual world behaviors, in particular in the area of serious games
  4. A greater variety of players and a better availability of data about players leads to the need for more variable and better customizable games, which require a more complex development process.

A solution for each of these issues can be found in the application of artificial-intelligence (AI) techniques to drive the design and development of games. From the perspective of AI-driven game design, AI supports or even takes over the role of the human game developer in creating particular elements of a game, and even complete new games.

While the game industry tends to use a small selection of well-known algorithms to generate elements of game worlds (in particular where graphics and animation are concerned), the use of AI to create new environments, new behaviors of virtual characters, new narratives, new game rules, or even new gameplay mechanisms is at present limited to a very small number of researchers. We see it, however, as the main direction in which innovation in game design and development can be found.

AI-driven game design sees applications in the design of virtual worlds, virtual characters, narratives, and game mechanics. Moreover, it can be used to assist in the human design process, and to adapt games automatically after publication. Finally, it can support the automated analysis of generated game elements. Each of these topics is a research domain by itself, which requires an interdisciplinary approach which borrows from computer science, psychology, cognitive science, and even the creative arts. A common ground is found in artificial intelligence techniques, in particular machine learning.

For this seminar, we brought together computer scientists and creative experts with the common goals of gaining a deeper understanding of various aspects of games, and of further improving games, in particular by using AI-techniques used to generate games and game elements. The goal was to look beyond what is currently possible and in use, and take steps towards the future of AI-driven game development. Besides theoretical discussions, part of the seminar was spent on trying to achieve first practical results.

Reports on the discussions and results achieved are found on the following pages. All in all, the organizers and participants deemed the seminar a great success, and are eager to continue into some of the directions that were focused on during the week at Schloss Dagstuhl.

Copyright Elisabeth André, Michael Cook, Mike Preuß, and Pieter Spronck
Participants
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  • Elisabeth André (Universität Augsburg, DE) [dblp]
  • Dan Ashlock (University of Guelph, CA) [dblp]
  • Sander C.J. Bakkes (Tilburg University, NL)
  • Rafael Bidarra (TU Delft, NL) [dblp]
  • Cameron Browne (RIKEN - Tokyo, JP) [dblp]
  • Alex J. Champandard (AiGameDev.com KG - Wien, AT) [dblp]
  • Simon Colton (Falmouth University, GB) [dblp]
  • Michael Cook (University of London, GB) [dblp]
  • Peter I. Cowling (University of York, GB) [dblp]
  • Steve Dahlskog (Malmö University, SE) [dblp]
  • Reynald Francois (Ubisoft - Düsseldorf, DE)
  • Matthew J. Guzdial (Georgia Institute of Technology - Atlanta, US) [dblp]
  • Amy K. Hoover (NJIT - Newark, US) [dblp]
  • Pier Luca Lanzi (Polytechnic University of Milan, IT) [dblp]
  • Marc Erich Latoschik (Universität Würzburg, DE) [dblp]
  • Antonios Liapis (University of Malta - Msida, MT) [dblp]
  • Jialin Liu (Queen Mary University of London, GB) [dblp]
  • Simon M. Lucas (Queen Mary University of London, GB) [dblp]
  • Joshua Allen McCoy (University of California - Davis, US) [dblp]
  • Alexander Nareyek (Singapore, SG) [dblp]
  • Mark J. Nelson (Falmouth University, GB) [dblp]
  • Ana Paiva (INESC-ID - Porto Salvo, PT) [dblp]
  • Mirjam Palosaari Eladhari (Södertörn University - Huddinge, SE) [dblp]
  • Diego Perez Liebana (University of Essex - Colchester, GB) [dblp]
  • Mike Preuß (Universität Münster, DE) [dblp]
  • Sebastian Risi (IT University of Copenhagen, DK) [dblp]
  • Spyridon Samothrakis (University of Essex - Colchester, GB) [dblp]
  • Jacob Schrum (Southwestern University - Georgetown, US) [dblp]
  • Emily Short (Oxford, GB) [dblp]
  • Adam M. Smith (University of California - Santa Cruz, US) [dblp]
  • Gillian Smith (Worcester Polytechnic Institute, US) [dblp]
  • Pieter Spronck (Tilburg University, NL) [dblp]
  • Anne Sullivan (University of Central Florida - Orlando, US) [dblp]
  • Shoshannah Tekofsky (Spirit AI - London, GB) [dblp]
  • Tommy Thompson (Anglia Ruskin University - Cambridge, GB) [dblp]
  • David Thue (Reykjavik University, IS) [dblp]
  • Julian Togelius (New York University, US) [dblp]
  • Michael Treanor (American University - Washington, US) [dblp]
  • Vanessa Volz (TU Dortmund, DE) [dblp]
  • Georgios N. Yannakakis (University of Malta - Msida, MT) [dblp]
  • R. Michael Young (University of Utah - Salt Lake City, US) [dblp]
  • G. Michael Youngblood (Xerox PARC - Palo Alto, US) [dblp]
  • Jichen Zhu (Drexel Univ. - Philadelphia, US) [dblp]
Related Seminars
  • Dagstuhl Seminar 12191: Artificial and Computational Intelligence in Games (2012-05-06 - 2012-05-11) (Details)
  • Dagstuhl Seminar 15051: Artificial and Computational Intelligence in Games: Integration (2015-01-25 - 2015-01-30) (Details)
  • Dagstuhl Seminar 19511: Artificial and Computational Intelligence in Games: Revolutions in Computational Game AI (2019-12-15 - 2019-12-20) (Details)
  • Dagstuhl Seminar 22251: Human-Game AI Interaction (2022-06-19 - 2022-06-24) (Details)
  • Dagstuhl Seminar 24261: Computational Creativity for Game Development (2024-06-23 - 2024-06-28) (Details)
Classification
  • artificial intelligence / robotics
  • modelling / simulation
  • multimedia
Keywords
  • multi-agent systems
  • game design
  • serious games
  • entertainment modeling
  • dynamical systems
Seminar 17471
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