Towards believable resource gathering behaviours in real-time strategy games with a memetic ant colony system

In this paper, the resource gathering problem in real-time strategy (RTS) games, is modeled as a path-finding problem where game agents responsible for gathering resources, also known as harvesters, are only equipped with the knowledge of its immediate sur- roundings and must gather knowledge about...

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Main Authors: Lim, Meng-Hiot, Chen, Xianshun, Ong, Yew Soon, Feng, Liang, Chen, Caishun, Ho, Choon Sing
其他作者: School of Computer Engineering
格式: Conference or Workshop Item
語言:English
出版: 2014
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在線閱讀:https://hdl.handle.net/10356/102917
http://hdl.handle.net/10220/19158
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機構: Nanyang Technological University
語言: English
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總結:In this paper, the resource gathering problem in real-time strategy (RTS) games, is modeled as a path-finding problem where game agents responsible for gathering resources, also known as harvesters, are only equipped with the knowledge of its immediate sur- roundings and must gather knowledge about the dynamics of the navigation graph that it resides on by sharing information and cooperating with other agents in the game environment. This paper proposed the conceptual modeling of a memetic ant colony system (MACS) for believable resource gathering in RTS games. In the proposed MACS, the harvester's path-finding and resource gathering knowledge captured are extracted and represented as memes, which are internally encoded as state transition rules (mem- otype), and externally expressed as ant pheromone on the graph edge (sociotype). Through the inter-play between the memetic evolution and ant colony, harvesters as memetic automatons spawned from an ant colony are able to acquire increasing level of capability in exploring complex dynamic game environment and gathering resources in an adaptive manner, producing consistent and impressive resource gathering behaviors.