活动时间:2019-6-11 13:30
活动地点:济事楼 455
PCG Research in GAME Lab
戴文凯
台湾科技大学资讯工程学系教授
邀请人:贾金原 教授
Abstract:
Computer games are already a part of our lives. To have players engaged in gaming worlds, the demand for human-like Bot, new, novel and even player-customized and/or adaptive content keeps increasing, especially when matching players is required, and manual content production is expensive, unscalable, and not time-to-market.
Procedural Content Generation (PCG) for Games is something that generates game content through algorithmic means to effectively and efficiently increase gameplay experience with creative, variant and adaptive content, and reduce production cost and effort. In recent three years, we, GAME Lab, have proposed methods used for procedurally generating game content, such as game level and game object, with an emphasis on commercial applications. On game level generation, our methods control the gameplay experience with adaptive game levels for Match-3 Game, Slot Game, and Car Racing Game. Based on summarized rules from Chinese feature building properties, we develop a parameterized Chinese feature building generation tool and Chinese feature village tool for creating and evolving game content with Chinese style. Also, we devise a sword editing tool with learning capability to generate a series of swords in consistent with attributes of a game player.
Regarding to our research on Game Bot for Eight-ball and Mahjong, the proposed AI methods based on heuristic rules, MCTS, and machine learning with scalable game bot strength will share with you about the current research status and possible future research directions.
Bio:
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