Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Queue - Game Development
Using multi-agent potential fields in real-time strategy games
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Optimizing strategy parameters in a game bot
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
A novel agent based control scheme for RTS games
Proceedings of The 8th Australasian Conference on Interactive Entertainment: Playing the System
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Bots for real-time strategy (RTS) games may be very challenging to implement. A bot controls a number of units that will have to navigate in a partially unknown environment, while at the same time avoid each other, search for enemies, and coordinate attacks to fight them down. Potential fields are a technique originating from the area of robotics where it is used in controlling the navigation of robots in dynamic environments. Although attempts have been made to transfer the technology to the gaming sector, assumed problems with efficiency and high costs for implementation have made the industry reluctant to adopt it. We present a multiagent potential field-based bot architecture that is evaluated in two different real-time strategy game settings and compare them, both in terms of performance, and in terms of softer attributes such as configurability with other state-of-the-art solutions. We show that the solution is a highly configurable bot that can match the performance standards of traditional RTS bots. Furthermore, we show that our approach deals with Fog of War (imperfect information about the opponent units) surprisingly well. We also show that a multiagent potential field-based bot is highly competitive in a resource gathering scenario.