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tsuomela : bayes   13

Mapping the Origins and Expansion of the Indo-European Language Family
"There are two competing hypotheses for the origin of the Indo-European language family. The conventional view places the homeland in the Pontic steppes about 6000 years ago. An alternative hypothesis claims that the languages spread from Anatolia with the expansion of farming 8000 to 9500 years ago. We used Bayesian phylogeographic approaches, together with basic vocabulary data from 103 ancient and contemporary Indo-European languages, to explicitly model the expansion of the family and test these hypotheses. We found decisive support for an Anatolian origin over a steppe origin. Both the inferred timing and root location of the Indo-European language trees fit with an agricultural expansion from Anatolia beginning 8000 to 9500 years ago. These results highlight the critical role that phylogeographic inference can play in resolving debates about human prehistory."
languages  linguistics  modeling  bayes  statistics  geography  anthropology 
august 2012 by tsuomela
Updating, part 1: When can you change your mind? The binary model - Less Wrong
To find out, I built a model of updating in response to the opinions of others.  It did, eventually, show that Bayesians improve their collective opinions by updating in response to the opinions of other Bayesians.  But this turns out not to depend on them satisfying the conditions of Aumann's theorem, or on doing Bayesian updating.  It depends only on a very simple condition, established at the start of the simulation.  Can you guess what it is?
bayes  model  agent-based-model  rationality 
september 2010 by tsuomela
[cs/0406061] The Complexity of Agreement
A celebrated 1976 theorem of Aumann asserts that honest, rational Bayesian agents with common priors will never "agree to disagree": if their opinions about any topic are common knowledge, then those opinions must be equal. Economists have written numerous papers examining the assumptions behind this theorem. But two key questions went unaddressed: first, can the agents reach agreement after a conversation of reasonable length? Second, can the computations needed for that conversation be performed efficiently? This paper answers both questions in the affirmative, thereby strengthening Aumann's original conclusion.
reasoning  rationality  bayes  probability  philosophy  agreement  disagreement 
may 2009 by tsuomela
Overcoming Bias: The Mechanics of Disagreement
Two ideal Bayesians cannot have common knowledge of disagreement
philosophy  argument  disagreement  bayes  probability  rationality 
december 2008 by tsuomela

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