Tito's Blog

Brain reasoning, bayesian networks, abstraction and Markov chains

Surely just reinventing the wheel here, but human brain looks like a sophisticated bayesian Markov chain machine with abstraction capabilities.

It is a Markov chain machine in the sense that our brain, through learning and experience, builds and updates over time a large matrix of conditional probabilities. By counting the number of instances of concurrent events A, B, C, …, I, X in real life, the brain constantly updates the probability of outcome X given the occurrence of A, B, C, …, I. Or in mathematical terms, P(X|A,B,C,…I).

Abstraction capabilities allow then the brain to build upon fundamental conditional probabilities P1, P2, P3, Px based on direct experiences, to create a second, third and iteratively n-th layer of more complex probabilities, for example P(Px|P1,P2,P3,…).

This wealth of information could be encode in chromosome-like strings to be passed on and further processed.

Japan’s Not So Lost Decade

Japan is not that bad after all when compared to the US.

Euro Government Bonds Monthly Redemption Calendar 2012

Now you can scare your friends at dinner hinting at the hundreds of billion euros of government debt coming due every month in Europe in 2012. Happy new year!

Source: Goldman Sachs via ZeroHedge.