Improving Companion Ai in Small-scale Attrition Games

نویسنده

  • Shuo Xu
چکیده

Artificial Intelligence (AI) has been widely used in modern video games for creating interactive non-player characters (NPC) and opponents. Although the design of NPC enemy AI has been studied for years and has many commercial implementations such as StarCraft, World of Warcraft, a good AI for NPC companions is still under-analyzed. In this thesis we investigate several approaches for solving companion decision problems in small-scale attrition games that involve two teams competing to eliminate the other. Then by introducing an action oriented analytical model, we analyze specific combat choices and improve the existing greedy heuristics. Our experimental results show that the improved heuristics indeed achieve better performance under various combat scenarios.

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تاریخ انتشار 2015