• Korean Journal of Logic
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• v.13 no.1
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• pp.21-52
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• 2010

What van Fraassen calls 'Reflection Principle' is claimed to meet several counterexamples, one of which stands out in the form of the Sleeping Beauty problem. Adam Elga argues that what he believes is the correct answer to the Sleeping Beauty problem shows that Reflection is subject to counterexamples. David Lewis proposes a different answer which preserves Reflection intact. Recently, Nick Bostrom presents a hybrid view which is supposed to allow us to keep Reflection. In proposing his hybrid view Bostrom criticizes both Elga and Lewis while taking some 'good' parts from each. He claims that Elga's view is not entirely acceptable because it presupposes the 'Self-Indication Assumption'. I shall claim, however, that Elga could avoid Bostrom's criticisms by introducing Bostrom's notion of agent-part. I believe that several probability-related puzzles including the Sleeping Beauty problem indicate a promising view concerning the way we should regard our future selves' opinions. According to this view, whether one takes the outsider stance or insider stance makes a difference in an important way that one and the same proposition is associated with different degrees of belief by one agent.

• The KIPS Transactions:PartC
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• v.10C no.1
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• pp.51-60
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• 2003

One of the most important matters in designing network and realizing service, is to grip on the traffic characteristics. Conventional traffic prediction and analysis used the models which based on the Poisson or Markovian. Recently, experimental research on the LAN, WAN and VBR traffic properties have been pointed rut that they weren't able to display actual real traffic specificities because the models based on the Poisson assumption had been underestimated the long range dependency of network traffic and self-similar peculiarities, it has been lately presented that the new approach method using self-similarity characteristics as similar as the real traffic models. Therefore, in this paper, we generated self-similar data traffic like real traffic as background load. On the existing ABR congestion control algorithm, we analyzed by classify into ACR, buffer utilization. cell drop rate, transmission throughput with the representative EFCI, ERICA, EPRCA and NIST twitch algorithm to show the efficient reaction about the burst traffic.