A Multiagent Potential Field-Based Bot for Real-Time Strategy Games

Document type: Journal Articles
Article type: Original article
Peer reviewed: Yes
Full text:
Author(s): Johan Hagelbäck, Stefan J. Johansson
Title: A Multiagent Potential Field-Based Bot for Real-Time Strategy Games
Journal: International Journal of Computer Games Technology
Year: 2009
Volume: 2009
Pagination: 10
ISSN: 1687-7055
Publisher: Hindawi Publishing Corporation
URI/DOI: 10.1155/2009/910819
Organization: Blekinge Institute of Technology
Department: School of Computing (Sektionen för datavetenskap och kommunikation)
School of Computing S-371 79 Karlskrona
+46 455 38 50 00
http://www.bth.se/com
Authors e-mail: johan.hagelback@bth.se, stefan.johansson@bth.se
Language: English
Abstract: 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.
Subject: Computer Science\Artificial Intelligence
Digital Game Development\General
Keywords: Agents, Swarm Intelligence, Emergent Behavior, Computer Games
Note: Open Access Journal Article ID 910819
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