June 28, 2010
Newcomb’s paradox posits a game with a transparent box containing $1 and an opaque box containing either $0 or $1,000. A Player is offered the choice between only the opaque box or both boxes. Before the Player makes this choice, a Predictor has attempted to predict the Player’s choice. The Predictor puts $1,000 into the opaque box, if the prediction is that only this box will be chosen. Otherwise, the Predictor puts $0.
The Predictor neither has a time machine nor some gift for backward causation. It is assumed, however, that the Predictor is rather reliable, though not necessarily infallible. Should the Player choose the opaque box only or both boxes? Read the rest of this entry »
June 22, 2010
There’s a debate in linguistics on the extent to which humans acquire language via learning and statistical generalization and the extent to which language acquisition aided by innate biases. Theoretical arguments have been devised to demonstrate that general-purpose learning would require to much data and that innate bias is necessary. An eprint claims to provide mathematical and empirical support against such impossibility results and in favor of the possibility of language acquisition through general-purpose learning. The learning method being advanced is a Minimum Description Length type method.
A. S. Hsu, N. Chater and P. M. B. Vitanyi. The probabilistic analysis of language acquisition: Theoretical, computational, and experimental analysis. arXiv:1006.3271 (2010)
June 21, 2010
A while back I noted an interesting paper about the arrow of time and memory loss in quantum mechanics. Unfortunately for that idea a new commentary by Jennings and Rudolph [PRL 104:148901, 2010] refutes it by exhibiting a counter-example.
June 21, 2010
A new survey sheds more light on who the anthropogenic global warming contrarians are. The abstract is self-explanatory and the fulltext is open access.
W. R. L. Anderegg et al. Expert credibility in climate change. PNAS, doi: 10.1073/pnas.1003187107
Abstract: Although preliminary estimates from published literature and expert surveys suggest striking agreement among climate scientists on the tenets of anthropogenic climate change (ACC), the American public expresses substantial doubt about both the anthropogenic cause and the level of scientific agreement underpinning ACC. A broad analysis of the climate scientist community itself, the distribution of credibility of dissenting researchers relative to agreeing researchers, and the level of agreement among top climate experts has not been conducted and would inform future ACC discussions. Here, we use an extensive dataset of 1,372 climate researchers and their publication and citation data to show that (i) 97–98% of the climate researchers most actively publishing in the field support the tenets of ACC outlined by the Intergovernmental Panel on Climate Change, and (ii) the relative climate expertise and scientific prominence of the researchers unconvinced of ACC are substantially below that of the convinced researchers.