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Documents authored by Congdon, Clare Bates

Document
DOI: 10.4230/DFU.Vol6.12191.33
Learning and Game AI

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

Published in: Dagstuhl Follow-Ups, Volume 6, Artificial and Computational Intelligence in Games (2013)

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
DOI: 10.4230/DFU.Vol6.12191.77
General Video Game Playing

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

Published in: Dagstuhl Follow-Ups, Volume 6, Artificial and Computational Intelligence in Games (2013)

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
DOI: 10.4230/DFU.Vol6.12191.101
Artificial and Computational Intelligence for Games on Mobile Platforms

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

Published in: Dagstuhl Follow-Ups, Volume 6, Artificial and Computational Intelligence in Games (2013)

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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