Determining Solution Space Characteristics for Real-Time Strategy Games and Characterizing Winning Strategies
The underlying goal of a competing agent in a discrete real-time strategy (RTS) game is to defeat an adversary. Strategic agents or participants must define an a priori plan to maneuver their resources in order to destroy the adversary and the adv...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2011-01-01
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| Series: | International Journal of Computer Games Technology |
| Online Access: | http://dx.doi.org/10.1155/2011/834026 |
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| Summary: | The underlying goal of a competing agent in a
discrete real-time strategy (RTS) game is to
defeat an adversary. Strategic agents or
participants must define an a priori plan
to maneuver their resources in order to destroy the adversary and
the adversary's resources as well as secure physical regions
of the environment. This a priori plan can be generated by
leveraging collected historical knowledge about the environment.
This knowledge is then employed in the generation of a
classification model for real-time decision-making in the RTS
domain. The best way to generate a classification model for a
complex problem domain depends on the characteristics of the
solution space. An experimental method to determine solution space
(search landscape) characteristics is through analysis of
historical algorithm performance for solving the specific problem.
We select a deterministic search technique and a stochastic search
method for a priori classification model generation. These
approaches are designed, implemented, and tested for a specific
complex RTS game, Bos Wars. Their performance allows us to draw
various conclusions about applying a competing agent in complex
search landscapes associated with RTS games. |
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| ISSN: | 1687-7047 1687-7055 |