Using multi-agent potential fields in real-time strategy games

ABSTRACT

Bots for Real Time Strategy (Rts) games provide a rich challenge to implement. A bot controls a number of units that may have to navigate in a partially unknown environment, while at the same time search for enemies and coordinate attacks to fight them down. Potential fields is 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 Multi-agent Potential Field based bot architecture that is evaluated in a real time strategy game setting and compare it, both in terms of performance, and in terms of softer attributes such as configurability with other state-of-the-art solutions. Although our solution did not reach the performance standards of traditional Rts bots in the test, we see great unexploited benefits in using multi-agent potential field based solutions in Rts games.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Multiagent systems

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems
          Subjects: Games

General Terms:
Algorithms, Design, Performance

Keywords:
Orts, Rts games, artificial potential fields, multi-agent bot