A Multi-agent Potential Field based bot for a Full RTS Game Scenario
2009 (English)Conference paper (Refereed)
Computer games in general, and Real Time Strategy games in particular is a challenging task for both AI research and game AI programmers. The player, or AI bot, must use its workers to gather resources. They must be spent wisely on structures such as barracks or factories, mobile units such as soldiers, workers and tanks. The constructed units can be used to explore the game world, hunt down the enemy forces and destroy the opponent buildings. We propose a multi-agent architecture based on artificial potential fields for a full real time strategy scenario. We validate the solution by participating in a yearly open real time strategy game tournament and show that the bot, even though not using any form of path planning for navigation, is able to perform well and win the tournament.
Place, publisher, year, edition, pages
Association for the Advancement of Artificial Intelligence , 2009.
Swarm Intelligence, Emergent Behavior, Computer Games
Research subject Computer and Information Sciences Computer Science, Computer Science
IdentifiersURN: urn:nbn:se:lnu:diva-42372OAI: oai:DiVA.org:lnu-42372DiVA: diva2:805266
Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2009, Stanford