Neural Networks for Real-time Pathfinding in Computer Games
Ross Graham2004, The ITB Journal
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One of the greatest challenges in the design of realistic Artificial Intelligence (AI) in computer games is agent movement. Pathfinding strategies are usually employed as the core of any AI movement system. The two main components for basic real-time pathfinding are (i) travelling towards a specified goal and (ii) avoiding dynamic and static obstacles that may litter the path to this goal. The focus of this paper is how machine learning techniques, such as Artificial Neural Networks and Genetic Algorithms, can be used to enhance an AI agent’s ability to handle pathfinding in real-time by giving them an awareness of the virtual world around them through sensors. Thus the agents should be able to react in real-time to any dynamic changes that may occur in the game.
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The ITB Journal
Volume 5
Issue 1
Article 21
2004
Neural Networks for Real-time Pathfinding in Computer Games
Ross Graham
School oflnformatics and Engineering, Institute of Technology at Blanchardstown, Dublin l5.,
[email protected]
Hugh McCabe
School oflnformatics and Engineering, Institute of Technology at Blanchardstown, Dublin l5.
Stephen Sheridan
School oflnformatics and Engineering, Institute of Technology at Blanchardstown, Dublin l5.
Follow this and additional works at: https://arrow.tudublin.ie/itbj
Part of the Software Engineering Commons
Recommended Citation
Graham, Ross; McCabe, Hugh; and Sheridan, Stephen (2004) "Neural Networks for Real-time Pathfinding
in Computer Games," The ITB Journal: Vol. 5: Iss. 1, Article 21.
doi:10.21427/D71Q95
Available at: https://arrow.tudublin.ie/itbj/vol5/iss1/21
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the Ceased publication at ARROW@TU Dublin. It has
been accepted for inclusion in The ITB Journal by an
authorized administrator of ARROW@TU Dublin. For more
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