AQ Interactive Chooses xaitment for Pathfinding and Nav Mesh Generation

FOR IMMEDIATE RELEASE

 

 

Saarbrücken/Quierschied, Germany– October 5, 2010– xaitment GmbH / Inc., the leading artificial intelligence (AI) game tool provider for the video games and simulations industries, today announced a new licensing agreement with AQ Interactive based in Tokyo, Japan. AQ Interactive will use xaitment’s AI game tool xaitMap to develop its upcoming title for Xbox 360 and PS3.

 

xaitMap provides AQ Interactive with fast and robust pathfinding and automatic navigation mesh generation that can be used straight out of the box. Due to the tool’s unique features, AQ Interactive can produce multi-level navigation meshes and a cross-platform runtime for unlimited map sizes and game complexity. In addition, the xaitMap module also holds previously used navigation meshes in memory, speeding up AQ Interactive’s overall AI development. 

 

“Companies that choose xaitment, do so because they are guaranteed to continuously get the most updated, state-of-the-art technology and outstanding, reliable support,” said Markus Schneider, CEO of xaitment Inc.“For AQ Interactive this translates into peace of mind, knowing that with xaitMap they can quickly and efficiently build their lower level AI and go on to concentrate on details that make their game unique.”

 

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For more information, contact:

xaitment GmbH

Julia Ziemann

Communications

Phone: +49 (0) 6897 / 600 80-22

Fax: +49 (0) 6897 / 600 80-20

Email: julia.ziemann@xaitment.com

Web: www.xaitment.com

 

About xaitment

xaitment GmbH/Inc. is the world leader in AI game tools for the games and simulations industries. Founded in Germany in 2004, xaitment offers AI middleware that goes beyond pathfinding. xaitment's AI game tools enable developers, through easy-to-use graphical user interfaces, to create automatic navigation mesh builds, movement behaviors, crowd simulations, hierarchical probabilistic finite state machines, world descriptions, autonomic behaviors, and experience-based and inference-based learning behaviors for computer generated characters. For more information, visit www.xaitment.com.


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