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.
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.
Original language | English |
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Title of host publication | Artificial and Computational Intelligence in Games |
Editors | M. Simon, Lucas & Michael Mateas, Mike Preuss, Pieter Spronck, Julian Togelius |
Publisher | Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing |
Pages | 1-19 |
Volume | 6 |
ISBN (Print) | 978-3-939897-62-0 |
DOIs | |
State | Published - 2013 |
Keywords
- search algorithms
- real-time video games
- Monte Carlo tree search
- minimax search, game theory