Set here the film ISO sensitivity to use for simulating the film graininess.

The analogy is that these people in a room are the Higgs particles.

You have to normalize in the 2nd.

This is the essence of particle filters.

So, you get 2 versions of P2, perhaps even 3 versions of P2, depending on the probabilities.

It ignores measurements, because the measurement sets the weighting factor in this resampling process, but with only 1 particle the same particle will be resampled no matter what.

So it's a prediction a prediction of a new particle.

Same with this guy over here, and this guy might find itself over here.

Number of particles

Particles

Right, H.

And we came up with this analogy, and it seemed to work.

You know, for me a particle, oh, it looks

Well, thanks Drew. Great question.

Particle Fountain Screen Saver

Particle density

Film Grain

What I'll do next is to give you another program assignment.

It has a very small mass and negative electric charge.

In fact, it is completely uncertain as to where it is.

We're creating a new set of particles called P3 it's an empty set in the beginning, and inside this routine, every time I resample,

We resample. We do forward prediction.

Particle Gravity Screen Saver

Particle size

One or both, who knows? Or it could be something completely different.

And less sunlight reaching the surface would tend to cool the planet.

In question 3 I'd like to quiz your intuition.

This is strands of magnetic field.

Now let's look into particle filters, the subject of today's class, and it's really interesting to see the answers for particle filters.

In the world of physics, they call appearance of the matter out of nothing,

What's that?

So that's the vector field in that area, or the force directed on that particle right when it's at that point.

I actually don't know.

Particle Fountain Setup

You see a higher density of particles over here and over here, than you see, for example, over here.

Thrun This is a great segue to one of the most successful algorithms in artificial intelligence and robotics called particle filters.

Intuitively speaking, each particle is a representation of a possible state, and the more consistent the particle with the measurement, the more the sonar measurement fits into the place where the particle says the robot is, the more likely it is to survive.

My specialty is particle physics.

The Higgs boson is an excitation of the Higgs field.

Now when a particle moves through the universe, it can interact with these Higgs particles.

Let's say I have it's huge like that, and I should have done it more proportionally, but I think you get the idea.

Over the past 10 years or so, I have worked on a number of different methods for buildings maps that are quite sophisticated,

Feynman said, Forget all of that.

Let me play this again.

To the extent that we look at gravitational interaction alone this is a dissipation less fluid.