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>> Welcome to the final week of the AI planning course.
I am glad you are still with us. On this course, you have already learned a
lot of things. I have described to you the planning
problem, and we have seen several algorithms for solving this problem,
including an algorithm that is behind one of the state-of-the-art planners, one of
the fastest plan-generating systems today. In this week, we're going to turn to less
technical material and go a lot broader. First, my colleague Austin Tate will
describe to you some practical planners and applications to which they have been
applied. People describe some of the inside
technology which hopefully you will recognize from what you have learned
previously. Then, in this week's feature, we will look
at planning for missions in space. Finally, I will describe to you some
topics that surround the planning problem we've looked at so far.
For example, what happens before we can plan, how we can come up with planning
domains? Or what happens after planning?
How do we do planned execution? And that will conclude the lectures for
this week and for the whole course. Then you still have to do the exams.
There is the awareness-level exam. There is the foundation-level exam.
And for those who want to pass the course at the performance level, you will also
have to do the final programming assignment.
And that's it.