That happens 37 of the time.

P of not A given the same events, X1, X2, and not X3, which resolves to P of not X3 given not A,

Then the value of the state for the action go up would be obtained as follows.

So the only thing we need to compute now is P of H given R.

Let's use the Laplacian smoother with K 1 to calculate the few interesting probabilities

Didn't I tell you not to come here?

Probability

Phil, the odds against

And these are mutually exclusive events, you can't have both of them

The gamma knife has a recurrence rate of over 13 percent.

If I pick a random T value, if I take a random T statistic

There's going to be a 10 percent chance you get a pretty good item.

Now let's have something a little bit more interesting.

We now apply Bayes rule.

What are the odds?

For example, in the last row we have a r and a t. r is 0.9.

Thrun The answer is a little bit involved.

The Probability of getting a heads(on any flip) is 0.6 and the probability of getting tails on the third flip is 0.4

least maybe it doesn't make intuitive sense just yet, but I showed you that the probability of a and b is equal to the probability of a given b times the probability of b.

Your rebirthday? Yeah.

In this case, there's only one such variable, Cloudy.

You wrote an algorithm that implements what's called Markov localization.

Better odds tonight?

Thrun As usual, we can resolve this using Bayes' rule.

Question 1 In the first question, I'm going to ask you some very basic probability questions.

I've got to do something new, I want to do something new.

Check again.

I'll make it right.

You might say OK, that's the probably of getting exactly 1 times the probability of getting 2 out of 3 plus the probability of getting 3 out of 3.

Probability of success

Probability of failure

And we get this, the probability of b given a is equal to this, probability of a given b.

Time the probability of two sided coin.

And it makes much more sense to talk about the probability or random variable equaling a value, or the probability that it is less than or greater than something or the probability that is has some property

The probability of getting one condition, of an object being a member of set A, or, or a member of set B, is equal to the probability that it is a member of set A, plus the probability that it is a member of set B, minus the probability that it is a member of both. minus the probability that it is a member of both.

So I'm going to flip it, and then I'm going to pick it up, and I'm going to flip it again.

The smallness of that probability is what we mean by extremity.

Let's talk about inaccurate robot motion.

In the second question we apply total probability.

Those values are discrete.

And this is the probability of four out of six heads, given an unfair coin.

So let's look at this, let's look at a population where the probability of success we'll define success as 1 as having a probability of p, and the probability of failure, the probability of failure is 1 minus p.

So is this a discrete or a continuous random variable?

How did we get this?

That happens in less than 2 of our missions.