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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

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

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.

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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}
}

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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.

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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}
}

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Search in Real-Time Video Games

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Learning and Game AI

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