In this paper, we investigate the influences of network delay on QoE (Quality of Experience) such as the operability of haptic interface device and the fairness between players for soft objects in a networked real-tim...In this paper, we investigate the influences of network delay on QoE (Quality of Experience) such as the operability of haptic interface device and the fairness between players for soft objects in a networked real-time game subjectively and objectively. We handle a networked balloon bursting game in which two players burst balloons (i.e., soft objects) in a 3D virtual space by using haptic interface devices, and the players compete for the number of burst balloons. As a result, we find that the operability depends on the network delay from the local terminal to the other terminal, and the fairness is mainly dependent on the difference in network delay between the players’ terminals. We confirm that there exists a trade-off relationship between the operability and the fairness. We also see that the contribution of the fairness is larger than that of the operability to the comprehensive quality (i.e., the weighted sum of the operability and fairness). Assessment results further show that the output timing of terminals should be adjusted to the terminal which has the latest output timing to maintain the fairness when the difference in network delay between the terminals is large. In this way, the comprehensive quality at each terminal can be maintained as high as possible.展开更多
Physical inactivity has been identified as one of the leading causes of many chronic diseases such as cardiovascular disease,type 2 diabetes,and obesity.Technology such as video games plays a complicated role in physi...Physical inactivity has been identified as one of the leading causes of many chronic diseases such as cardiovascular disease,type 2 diabetes,and obesity.Technology such as video games plays a complicated role in physical inactivity—much like a double-edged sword.Traditionally,video games have contributed to the epidemic of physical inactivity and have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In this paper, we investigate the influences of network delay on QoE (Quality of Experience) such as the operability of haptic interface device and the fairness between players for soft objects in a networked real-time game subjectively and objectively. We handle a networked balloon bursting game in which two players burst balloons (i.e., soft objects) in a 3D virtual space by using haptic interface devices, and the players compete for the number of burst balloons. As a result, we find that the operability depends on the network delay from the local terminal to the other terminal, and the fairness is mainly dependent on the difference in network delay between the players’ terminals. We confirm that there exists a trade-off relationship between the operability and the fairness. We also see that the contribution of the fairness is larger than that of the operability to the comprehensive quality (i.e., the weighted sum of the operability and fairness). Assessment results further show that the output timing of terminals should be adjusted to the terminal which has the latest output timing to maintain the fairness when the difference in network delay between the terminals is large. In this way, the comprehensive quality at each terminal can be maintained as high as possible.
文摘Physical inactivity has been identified as one of the leading causes of many chronic diseases such as cardiovascular disease,type 2 diabetes,and obesity.Technology such as video games plays a complicated role in physical inactivity—much like a double-edged sword.Traditionally,video games have contributed to the epidemic of physical inactivity and have
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.
