在阿克塞尔罗德锦标赛的最高分
Top Score in Axelrod Tournament
摘要：
该项目的重点将是在阿克塞尔罗德锦标赛获得最高分的考试。阿克塞尔罗德锦标赛最高分的最初设计包括查看阿克塞尔罗德库中当前顶级策略的合作率。在创建了一个利用顶级玩家合作率的初始有限状态机策略之后，我们的十状态FSM在Axelrod库中的短运行时间策略中的220个玩家中排名前35位。经过50代的快速进化算法，我们将原来的十状态FSM变成了八状态FSM，并在Axelrod库中的前5个短运行时间策略中完成。这个八状态FSM然后再次使用完整的进化算法过程，历时500代，其中八状态FSM进化成另一个八状态FSM，其在短运行时间策略和完整Axelrod锦标赛中在Axelrod库中获得第一名。从最终的FSM，八个状态中的两个是不可访问的，因此最终的FSM策略是六状态FSM，其在全阿克塞尔罗德锦标赛中首先完成，而不是短运行时间策略以及长运行时间策略。
英文摘要：
The focus of the project will be an examination of obtaining the highest score in the Axelrod Tournament. The initial design of the highest score in the Axelrod Tournament consisted of looking at the Cooperation rates of the top strategies currently in the Axelrod Library. After creating an initial Finite State Machine strategy that utilized the Cooperation Rates of the top players; our ten-state FSM finished within the top 35 players out of 220 in the short run time strategies in the Axelrod Library. After a quick evolutionary algorithm, 50 generations, our original ten-state FSM was changed into an eight-state FSM, which finished within the top 5 of the short run time strategies in the Axelrod Library. This eight-state FSM was then evolved again using a full evolutionary algortihm process, which lasted 500 generations, where the eight-state FSM evolved into a another eight-state FSM which finishes first in the Axelrod Library among the short run time strategies and the full Axelrod Tournament. From that final FSM, two of the eight states are inaccessible, so the final FSM strategy is a six-state FSM that finishes first in the Full Axelrod Tournament, against the short run time strategies as well as the long run time strategies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
