Virtual property has attained legal status with the recent conviction of several online thieves, but the issue remains a murky one Zhang Bin, a resident of Ningbo, in Zhejiang Province, began selling online game accou...Virtual property has attained legal status with the recent conviction of several online thieves, but the issue remains a murky one Zhang Bin, a resident of Ningbo, in Zhejiang Province, began selling online game accounts on the Internet in February 2005. Among his customers was a man surnamed Shen, who bought an account for 4,800 yuan. Several days later, Shen discovered that his account had been embezzled, and展开更多
介绍了实时流和实时流协议,针对基于实时协议的流媒体客户端播放器的特殊要求,提出了一种适用于视频点播(Video On Demand)的流媒体客户端结构模型,研究并设计了相应的流量控制策略、组包算法和缓存管理策略。试验结果表明,该客户端播...介绍了实时流和实时流协议,针对基于实时协议的流媒体客户端播放器的特殊要求,提出了一种适用于视频点播(Video On Demand)的流媒体客户端结构模型,研究并设计了相应的流量控制策略、组包算法和缓存管理策略。试验结果表明,该客户端播放器占用系统资 源少,具有良好的实时性、容错性和同步性。展开更多
This paper investigates the performance and the results of an evolutionary algorithm （EA） specifically designed for evolving the decision engine of a program （which, in this context, is called bot） that plays Plan...This paper investigates the performance and the results of an evolutionary algorithm （EA） specifically designed for evolving the decision engine of a program （which, in this context, is called bot） that plays Planet Wars. This game, which was chosen for the Google Artificial Intelligence Challenge in 2010, requires the bot to deal with multiple target planets, while achieving a certain degree of adaptability in order to defeat different opponents in different scenarios. The decision engine of the bot is initially based on a set of rules that have been defined after an empirical study, and a genetic algorithm （GA） is used for tuning the set of constants, weights and probabilities that those rules include, and therefore, the general behaviour of the bot. Then, the bot is supplied with the evolved decision engine and the results obtained when competing with other bots （a bot offered by Google as a sparring partner, and a scripted bot with a pre-established behaviour） are thoroughly analysed. The evaluation of the candidate solutions is based on the result of non-deterministic battles （and environmental interactions） against other bots, whose outcome depends on random draws as well as on the opponents＇ actions. Therefore, the proposed GA is dealing with a noisy fitness function. After analysing the effects of the noisy fitness, we conclude that tackling randomness via repeated combats and reevaluations reduces this effect and makes the GA a highly valuable approach for solving this problem.展开更多
文摘Virtual property has attained legal status with the recent conviction of several online thieves, but the issue remains a murky one Zhang Bin, a resident of Ningbo, in Zhejiang Province, began selling online game accounts on the Internet in February 2005. Among his customers was a man surnamed Shen, who bought an account for 4,800 yuan. Several days later, Shen discovered that his account had been embezzled, and
基金Andalusian Autonomous Government (Junta de Andalucía) under Project No. P08-TIC-03903,Ministerio de Ciencia e Innovación under Project No. TIN2011-28627-C04-02+1 种基金Foundation for Science and Technology(FCT) of Portugal (ISR/IST plurianual funding) through the PIDDAC Program fundsFCT,Ministério da Ci encia e Tecnologia, for his Research Fellowship under Grant No. SFRH/BPD/66876/2009
文摘This paper investigates the performance and the results of an evolutionary algorithm （EA） specifically designed for evolving the decision engine of a program （which, in this context, is called bot） that plays Planet Wars. This game, which was chosen for the Google Artificial Intelligence Challenge in 2010, requires the bot to deal with multiple target planets, while achieving a certain degree of adaptability in order to defeat different opponents in different scenarios. The decision engine of the bot is initially based on a set of rules that have been defined after an empirical study, and a genetic algorithm （GA） is used for tuning the set of constants, weights and probabilities that those rules include, and therefore, the general behaviour of the bot. Then, the bot is supplied with the evolved decision engine and the results obtained when competing with other bots （a bot offered by Google as a sparring partner, and a scripted bot with a pre-established behaviour） are thoroughly analysed. The evaluation of the candidate solutions is based on the result of non-deterministic battles （and environmental interactions） against other bots, whose outcome depends on random draws as well as on the opponents＇ actions. Therefore, the proposed GA is dealing with a noisy fitness function. After analysing the effects of the noisy fitness, we conclude that tackling randomness via repeated combats and reevaluations reduces this effect and makes the GA a highly valuable approach for solving this problem.
