Thrun So let's begin by taking the hidden out of the Markov model and study Markov chains.

It's applicable to many estimation problems, and it will be important going forward in this class.

This is a great moment where I can test whether you really think like an artificial intelligence person.

Thrun

In this final question, I'd like you to learn the position parameters of Markov chains.

So the answer here is the stationary distribution will have A occurring with 2 3 chance and B with 1 3 chance.

And that resolves simply to 0.4 if you work it all out.

This software carries out Markov Chain Monte Carlo calculations by the use of Gibbs Sampling.

That's like the fancy math notation, but what it really means is we just wait a long, long time.

It is Laplacian smoothing, which can be applied just exactly the same way we saw it in class in various contexts.

This is our sample for the initial state and all these transitinos over here are samples for the state transitions in this Markov chain.

Carbon chain c24.

In fact, I didn't even tell you what the initial state was.

Circles that makes life...

A place where you view pictures that coincide with your social life.

So you could write that as g1 prime of y.

The dots were connected in my life.

So y soon. prime is equal to what?

like a chain of falling dominoes.

This is difficult, maybe some type of trig function.

Markov chains that have that property, which are pretty much all Markov chains, are called ergodic.

Many like minded friends and I always share the mantra

So this is plus 6y squared.

So no one knows more about the cycle of violence Than I do.

That's basically it.

I hope nobody finds that offensive.

The Krell furnaces, chain reaction...

Even a few people leaving would reverberate through the entire user base. The users are interconnected. That is the whole point.

But this is great fun for children.

I thought that piling up something is so interesting.

We're gonna start a chain reaction.

Chief Agent Yuri Marklov.

But we didn't like these things here, so we essentially use our Navy to

Frogs are important for a multitude of reasons.

This idea is the same as that of building my sailing boat.

We're all links on the universal food chain.

Who died on new year's eve,1920.

And not in a way that would perpetuate the cycle of violence.

So one of the questions you might ask for a Markov chain like this is what happens if time becomes really large?

I'm Chief Agent Yuri Marklov of the F.S.B.

You know, Liv thinks I'm right... about there being chain reactions that led up to the crashes.

Because I don't want this to be completely mechanical.

When dinosaurs still ruled the planet.

So that's how I knew that this was the antiderivative.

Definitely in the water_BAR_and the food chain.