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Dagstuhl Follow-Ups, Volume 6

Artificial and Computational Intelligence in Games



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Publication Details

  • published at: 2013-11-18
  • Publisher: Schloss-Dagstuhl - Leibniz Zentrum für Informatik
  • ISBN: 978-3-939897-62-0
  • DBLP: db/conf/dagstuhl/dfu6

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Document
Complete Volume
DFU, Volume 6, Artificial and Computational Intelligence in Games, Complete Volume

Authors: Simon M. Lucas, Michael Mateas, Mike Preuss, Pieter Spronck, and Julian Togelius


Abstract
DFU, Volume 6, Artificial and Computational Intelligence in Games, Complete Volume

Cite as

Simon M. Lucas, Michael Mateas, Mike Preuss, Pieter Spronck, and Julian Togelius. DFU, Volume 6, Artificial and Computational Intelligence in Games, Complete Volume. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@Collection{DFU.Vol6.12191,
  title =	{{DFU, Volume 6, Artificial and Computational Intelligence in Games, Complete Volume}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191},
  URN =		{urn:nbn:de:0030-drops-43518},
  doi =		{10.4230/DFU.Vol6.12191},
  annote =	{Keywords: Applications and Expert Systems: Games}
}
Document
Frontmatter

Authors: Simon M. Lucas, Michael Mateas, Mike Preuss, Pieter Spronck, and Julian Togelius


Abstract
Frontmatter, table of contents, preface, author list

Cite as

Simon M. Lucas, Michael Mateas, Mike Preuss, Pieter Spronck, and Julian Togelius. Frontmatter. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 0:i-0:xiv, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@InCollection{lucas_et_al:DFU.Vol6.12191.i,
  author =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  title =	{{Frontmatter}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{0:i--0:xiv},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.i},
  URN =		{urn:nbn:de:0030-drops-43315},
  doi =		{10.4230/DFU.Vol6.12191.i},
  annote =	{Keywords: Frontmatter, table of contents, preface, author list}
}
Document
Search in Real-Time Video Games

Authors: Peter I. Cowling, Michael Buro, Michal Bida, Adi Botea, Bruno Bouzy, Martin V. Butz, Philip Hingston, Hector Muñoz-Avila, Dana Nau, and Moshe Sipper


Abstract
This chapter arises from the discussions of an experienced international group of researchers interested in the potential for creative application of algorithms for searching finite discrete graphs, which have been highly successful in a wide range of application areas, to address a broad range of problems arising in video games. The chapter first summarises the state of the art in search algorithms for games. It then considers the challenges in implementing these algorithms in video games (particularly real time strategy and first-person games) and ways of creating searchable discrete representations of video game decisions (for example as state-action graphs). Finally the chapter looks forward to promising techniques which might bring some of the success achieved in games such as Go and Chess, to real-time video games. For simplicity, we will consider primarily the objective of maximising playing strength, and consider games where this is a challenging task, which results in interesting gameplay.

Cite as

Peter I. Cowling, Michael Buro, Michal Bida, Adi Botea, Bruno Bouzy, Martin V. Butz, Philip Hingston, Hector Muñoz-Avila, Dana Nau, and Moshe Sipper. Search in Real-Time Video Games. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 1-19, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@InCollection{cowling_et_al:DFU.Vol6.12191.1,
  author =	{Cowling, Peter I. and Buro, Michael and Bida, Michal and Botea, Adi and Bouzy, Bruno and Butz, Martin V. and Hingston, Philip and Mu\~{n}oz-Avila, Hector and Nau, Dana and Sipper, Moshe},
  title =	{{Search in Real-Time Video Games}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{1--19},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.1},
  URN =		{urn:nbn:de:0030-drops-43328},
  doi =		{10.4230/DFU.Vol6.12191.1},
  annote =	{Keywords: search algorithms, real-time video games, Monte Carlo tree search, minimax search, game theory}
}
Document
Pathfinding in Games

Authors: Adi Botea, Bruno Bouzy, Michael Buro, Christian Bauckhage, and Dana Nau


Abstract
Commercial games can be an excellent testbed to artificial intelligence (AI) research, being a middle ground between synthetic, highly abstracted academic benchmarks, and more intricate problems from real life. Among the many AI techniques and problems relevant to games, such as learning, planning, and natural language processing, pathfinding stands out as one of the most common applications of AI research to games. In this document we survey recent work in pathfinding in games. Then we identify some challenges and potential directions for future work. This chapter summarizes the discussions held in the pathfinding workgroup.

Cite as

Adi Botea, Bruno Bouzy, Michael Buro, Christian Bauckhage, and Dana Nau. Pathfinding in Games. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 21-31, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@InCollection{botea_et_al:DFU.Vol6.12191.21,
  author =	{Botea, Adi and Bouzy, Bruno and Buro, Michael and Bauckhage, Christian and Nau, Dana},
  title =	{{Pathfinding in Games}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{21--31},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.21},
  URN =		{urn:nbn:de:0030-drops-43334},
  doi =		{10.4230/DFU.Vol6.12191.21},
  annote =	{Keywords: path finding, search, games}
}
Document
Learning and Game AI

Authors: Hector Muñoz-Avila, Christian Bauckhage, Michal Bida, Clare Bates Congdon, and Graham Kendall


Abstract
The incorporation of learning into commercial games can enrich the player experience, but may concern developers in terms of issues such as losing control of their game world. We explore a number of applied research and some fielded applications that point to the tremendous possibilities of machine learning research including game genres such as real-time strategy games, flight simulation games, car and motorcycle racing games, board games such as Go, an even traditional game-theoretic problems such as the prisoners dilemma. A common trait of these works is the potential of machine learning to reduce the burden of game developers. However a number of challenges exists that hinder the use of machine learning more broadly. We discuss some of these challenges while at the same time exploring opportunities for a wide use of machine learning in games.

Cite as

Hector Muñoz-Avila, Christian Bauckhage, Michal Bida, Clare Bates Congdon, and Graham Kendall. Learning and Game AI. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 33-43, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@InCollection{munozavila_et_al:DFU.Vol6.12191.33,
  author =	{Mu\~{n}oz-Avila, Hector and Bauckhage, Christian and Bida, Michal and Congdon, Clare Bates and Kendall, Graham},
  title =	{{Learning and Game AI}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{33--43},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.33},
  URN =		{urn:nbn:de:0030-drops-43348},
  doi =		{10.4230/DFU.Vol6.12191.33},
  annote =	{Keywords: Games, machine learning, artificial intelligence, computational intelligence}
}
Document
Player Modeling

Authors: Georgios N. Yannakakis, Pieter Spronck, Daniele Loiacono, and Elisabeth André


Abstract
Player modeling is the study of computational models of players in games. This includes the detection, modeling, prediction and expression of human player characteristics which are manifested through cognitive, affective and behavioral patterns. This chapter introduces a holistic view of player modeling and provides a high level taxonomy and discussion of the key components of a player's model. The discussion focuses on a taxonomy of approaches for constructing a player model, the available types of data for the model's input and a proposed classification for the model's output. The chapter provides also a brief overview of some promising applications and a discussion of the key challenges player modeling is currently facing which are linked to the input, the output and the computational model.

Cite as

Georgios N. Yannakakis, Pieter Spronck, Daniele Loiacono, and Elisabeth André. Player Modeling. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 45-59, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@InCollection{yannakakis_et_al:DFU.Vol6.12191.45,
  author =	{Yannakakis, Georgios N. and Spronck, Pieter and Loiacono, Daniele and Andr\'{e}, Elisabeth},
  title =	{{Player Modeling}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{45--59},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.45},
  URN =		{urn:nbn:de:0030-drops-43351},
  doi =		{10.4230/DFU.Vol6.12191.45},
  annote =	{Keywords: User modeling, Computer Games, Computational and Artificial Intelligence, Affective Computing}
}
Document
Procedural Content Generation: Goals, Challenges and Actionable Steps

Authors: Julian Togelius, Alex J. Champandard, Pier Luca Lanzi, Michael Mateas, Ana Paiva, Mike Preuss, and Kenneth O. Stanley


Abstract
This chapter discusses the challenges and opportunities of procedural content generation (PCG) in games. It starts with defining three grand goals of PCG, namely multi-level multicontent PCG, PCG-based game design and generating complete games. The way these goals are defined, they are not feasible with current technology. Therefore we identify nine challenges for PCG research. Work towards meeting these challenges is likely to take us closer to realising the three grand goals. In order to help researchers get started, we also identify five actionable steps, which PCG researchers could get started working on immediately.

Cite as

Julian Togelius, Alex J. Champandard, Pier Luca Lanzi, Michael Mateas, Ana Paiva, Mike Preuss, and Kenneth O. Stanley. Procedural Content Generation: Goals, Challenges and Actionable Steps. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 61-75, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@InCollection{togelius_et_al:DFU.Vol6.12191.61,
  author =	{Togelius, Julian and Champandard, Alex J. and Lanzi, Pier Luca and Mateas, Michael and Paiva, Ana and Preuss, Mike and Stanley, Kenneth O.},
  title =	{{Procedural Content Generation: Goals, Challenges and Actionable Steps}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{61--75},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.61},
  URN =		{urn:nbn:de:0030-drops-43367},
  doi =		{10.4230/DFU.Vol6.12191.61},
  annote =	{Keywords: procedural content generation, video games}
}
Document
General Video Game Playing

Authors: John Levine, Clare Bates Congdon, Marc Ebner, Graham Kendall, Simon M. Lucas, Risto Miikkulainen, Tom Schaul, and Tommy Thompson


Abstract
One of the grand challenges of AI is to create general intelligence: an agent that can excel at many tasks, not just one. In the area of games, this has given rise to the challenge of General Game Playing (GGP). In GGP, the game (typically a turn-taking board game) is defined declaratively in terms of the logic of the game (what happens when a move is made, how the scoring system works, how the winner is declared, and so on). The AI player then has to work out how to play the game and how to win. In this work, we seek to extend the idea of General Game Playing into the realm of video games, thus forming the area of General Video Game Playing (GVGP). In GVGP, computational agents will be asked to play video games that they have not seen before. At the minimum, the agent will be given the current state of the world and told what actions are applicable. Every game tick the agent will have to decide on its action, and the state will be updated, taking into account the actions of the other agents in the game and the game physics. We envisage running a competition based on GVGP playing, using arcadestyle (e.g. similar to Atari 2600) games as our starting point. These games are rich enough to be a formidable challenge to a GVGP agent, without introducing unnecessary complexity. The competition that we envisage could have a number of tracks, based on the form of the state (frame buffer or object model) and whether or not a forward model of action execution is available. We propose that the existing Physical Travelling Salesman (PTSP) software could be extended for our purposes and that a variety of GVGP games could be created in this framework by AI and Games students and other developers. Beyond this, we envisage the development of a Video Game Description Language (VGDL) as a way of concisely specifying video games. For the competition, we see this as being an interesting challenge in terms of deliberative search, machine learning and transfer of existing knowledge into new domains.

Cite as

John Levine, Clare Bates Congdon, Marc Ebner, Graham Kendall, Simon M. Lucas, Risto Miikkulainen, Tom Schaul, and Tommy Thompson. General Video Game Playing. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 77-83, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@InCollection{levine_et_al:DFU.Vol6.12191.77,
  author =	{Levine, John and Congdon, Clare Bates and Ebner, Marc and Kendall, Graham and Lucas, Simon M. and Miikkulainen, Risto and Schaul, Tom and Thompson, Tommy},
  title =	{{General Video Game Playing}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{77--83},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.77},
  URN =		{urn:nbn:de:0030-drops-43374},
  doi =		{10.4230/DFU.Vol6.12191.77},
  annote =	{Keywords: Video games, artificial intelligence, artificial general intelligence}
}
Document
Towards a Video Game Description Language

Authors: Marc Ebner, John Levine, Simon M. Lucas, Tom Schaul, Tommy Thompson, and Julian Togelius


Abstract
This chapter is a direct follow-up to the chapter on General Video Game Playing (GVGP). As that group recognised the need to create a Video Game Description Language (VGDL), we formed a group to address that challenge and the results of that group is the current chapter. Unlike the VGDL envisioned in the previous chapter, the language envisioned here is not meant to be supplied to the game-playing agent for automatic reasoning; instead we argue that the agent should learn this from interaction with the system. The main purpose of the language proposed here is to be able to specify complete video games, so that they could be compiled with a special VGDL compiler. Implementing such a compiler could provide numerous opportunities; users could modify existing games very quickly, or have a library of existing implementations defined within the language (e.g. an Asteroids ship or a Mario avatar) that have pre-existing, parameterised behaviours that can be customised for the users specific purposes. Provided the language is fit for purpose, automatic game creation could be explored further through experimentation with machine learning algorithms, furthering research in game creation and design. In order for both of these perceived functions to be realised and to ensure it is suitable for a large user base we recognise that the language carries several key requirements. Not only must it be human-readable, but retain the capability to be both expressive and extensible whilst equally simple as it is general. In our preliminary discussions, we sought to define the key requirements and challenges in constructing a new VGDL that will become part of the GVGP process. From this we have proposed an initial design to the semantics of the language and the components required to define a given game. Furthermore, we applied this approach to represent classic games such as Space Invaders, Lunar Lander and Frogger in an attempt to identify potential problems that may come to light. Work is ongoing to realise the potential of the VGDL for the purposes of Procedural Content Generation, Automatic Game Design and Transfer Learning.

Cite as

Marc Ebner, John Levine, Simon M. Lucas, Tom Schaul, Tommy Thompson, and Julian Togelius. Towards a Video Game Description Language. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 85-100, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@InCollection{ebner_et_al:DFU.Vol6.12191.85,
  author =	{Ebner, Marc and Levine, John and Lucas, Simon M. and Schaul, Tom and Thompson, Tommy and Togelius, Julian},
  title =	{{Towards a Video Game Description Language}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{85--100},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.85},
  URN =		{urn:nbn:de:0030-drops-43385},
  doi =		{10.4230/DFU.Vol6.12191.85},
  annote =	{Keywords: Video games, description language, language construction}
}
Document
Artificial and Computational Intelligence for Games on Mobile Platforms

Authors: Clare Bates Congdon, Philip Hingston, and Graham Kendall


Abstract
In this chapter, we consider the possibilities of creating new and innovative games that are targeted for mobile devices, such as smart phones and tablets, and that showcase AI (Artificial Intelligence) and CI (Computational Intelligence) approaches. Such games might take advantage of the sensors and facilities that are not available on other platforms, or might simply rely on the "app culture" to facilitate getting the games into users' hands. While these games might be profitable in themselves, our focus is on the benefits and challenges of developing AI and CI games for mobile devices.

Cite as

Clare Bates Congdon, Philip Hingston, and Graham Kendall. Artificial and Computational Intelligence for Games on Mobile Platforms. In Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, Volume 6, pp. 101-108, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2013)


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@InCollection{congdon_et_al:DFU.Vol6.12191.101,
  author =	{Congdon, Clare Bates and Hingston, Philip and Kendall, Graham},
  title =	{{Artificial and Computational Intelligence for Games on Mobile Platforms}},
  booktitle =	{Artificial and Computational Intelligence in Games},
  pages =	{101--108},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-62-0},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{6},
  editor =	{Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.101},
  URN =		{urn:nbn:de:0030-drops-43393},
  doi =		{10.4230/DFU.Vol6.12191.101},
  annote =	{Keywords: Games, mobile, artificial intelligence, computational intelligence}
}

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