Titlebook: Neural Information Processing; 21st International C Chu Kiong Loo,Keem Siah Yap,Kaizhu Huang Conference proceedings 2014 Springer Internati

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Takamitsu Araki,Hideitsu Hino,Shotaro Akahoearch to define real-number intelligence levels of complicated intelligent systems. Our agents are more idealized, which allows us to define a much simpler measure of intelligence level for them. In short, we define the intelligence level of a mechanical knowing agent to be the supremum of the compu

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Shuichi Kurogi,Takuya Ueki,Satoshi Takeguchi,Yuta Mizobeearch to define real-number intelligence levels of complicated intelligent systems. Our agents are more idealized, which allows us to define a much simpler measure of intelligence level for them. In short, we define the intelligence level of a mechanical knowing agent to be the supremum of the compu

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Hong Ji,Badong Chen,Zejian Yuan,Nanning Zheng,Andreas Keil,Jose C. Príncipeinformation flow (QIF) analyses quantify the amount of knowledge an attacker can gain on the secrets by observing the outputs. This paper presents a novel approach for calculating an upper bound for the leakage of confidential information in a program regarding min-entropy. The approach uses a data

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Yuki Ueyamaualitative properties, for example whether an intention completes. BDI-based systems, however, operate in uncertain environments with dynamic behaviours: we may need quantitative analysis to establish properties such as the probability of eventually completing an intention. We define a probabilistic

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Xi Yang,Kaizhu Huang,Rui Zhangualitative properties, for example whether an intention completes. BDI-based systems, however, operate in uncertain environments with dynamic behaviours: we may need quantitative analysis to establish properties such as the probability of eventually completing an intention. We define a probabilistic

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