Cheapest first, first we expand the path of length zero, then the path of length 2.

We could add in another path here of length two and another path here of length two.

Here is another path of length two.

Now there's a path of length 4, path of length 5, path of length 6, a path of length 7, and finally, a path of length 8.

Using the same bipartite graph, B, with 5 edges on the left and 3 edges on the right we ask what is the maximum possible path length in B?

Which path would you prefer?

Forget about the colors for a moment, and just think about the structure of binary trees.

Message route

And as we follow them, we build paths or sequences of actions.

So just being in Arad is the path of length zero, and now we could start exploring the space and add in this path of length one, this path of length one, and this path of length one.

Here is a path of length three.

Here's my next question. Suppose we optimize both at the same time with an appropriate alpha?

Two approaches?

In fact, it will, unless there isn't one.

The third question asked, what is the maximum possible path length in B?

lower bound on N in terms of k, let's have an upper bound on k in terms of N.

And I just have to add up.

And that is the case in flies.

DWing corridor where it intersects with CWing.

We know you're in there. Cover that intersection.

There's 2 ways I can get to this outcome.

All this falls all the way through the while loop is done and it returns false, so instead of actually returning a distance, it's going to return false meaning I wasn't able to find a path.

We're going to write now focus on a particular one which is the average shortest path length to all the other nodes.

Andrew Goldberg Recently I've been working a lot on shortest path algorithms, especially motivated by GPS navigation applications, so basically how to get from A to B.

Meet me on the corner of Santa Monica and Century West.

Now let me ask the exact same question just for the second criterion. Forget about the first one.

So now we've removed this path from the frontier, but we've added in 3 new paths.

It's how he got the tetanus into her system.

The path that goes from Arad to Sibiu and back to Arad is removed, and we are left with these one, two, three, four, five possible paths.

We call this the Human Connectome.

And the reason is that these hormones,

Yeah, well, that teenth got things rolling.

Now we're in a position where we have 3 paths on the frontier, and we have to pick the shortest one.

We look at all the actions from that state, and we add to the path the actions and the result of that state so we get a new path that has the old path, the action and the result of that action, and we stick all of those paths back onto the frontier.

Suppose your car like a robot right over here wished to get to right over here.

So we're going to add 3 paths.

Neural connections are formed.

If that's not the case, we're going to look at every node that is linked to from destination.

Now the question I want you to answer is once we remove that from the frontier, what paths are we going to add next?

And this slide shows you this.

If it's minimized, then all the y's are the same, which means you only get a single point, and we get no path at all.

Mrs. Clark is in Africa for two weeks with her church group.

The passage south is being watched.

Begin rerouting the targets.

So now we pull it off, do the goal test, and now we found our path to the goal, and it is, in fact, the shortest possible path.