AI class unit 8

These are my notes for unit 8 of the AI class.

Planning

Introduction

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Hi, and welcome back. This unit is about planning. We defined AI to be the study and process of finding appropriate actions for an agent. So in some sense planning is really the core of all of AI. The technique we looked at so far was problem solving search over a state space using techniques like A*.

Given a state space and a problem description, we can find a solution, a path to the goal. Those approaches are great for a variety of environments, but they only work when the environment is deterministic and fully observable.

In this unit, we will see how to relax those constraints.

Problem Solving vs Planning

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You remember how problem solving worked. We have a state space like this, and we're given a start state and a goal to reach, and then we'd search for a path to find that goal, and maybe we find this path. Now the way a problem solving agent would work, is first it does all the work to figure out the path to the goal just doing by thinking, and then it starts to execute that path, to drive or walk, however you want to get there, from the start state to the end state.

But think about what would happen if you did that in real life. If you did all your planning ahead of time, you had the complete goal, and then without interacting with the world, without sensing it at all, you started to execute that path. Well, this has in fact been studied. People have gone out and blindfolded walkers, put them in a field and told them to walk in a straight line, and the results are not pretty. Here are the GPS tracks to prove it.

So we take a hiker, we put him at a start location, say here, and we blindfold him so that he can't see anything in the horizon, but just has enough to see his or her feet so that they won't stumble over something, and tell them execute the plan of going forward. Put one foot in front of each other and walk forward in a straight line, and these are the typical paths we see. Start out going straight for a while, but then go in loop de loops and end up not at a straight path at all. These ones over here, starting in this location, are even more convoluted. They get going straight for a little bit and then go in very tight loops.

So people are incapable of walking a straight line without any feedback from the environment. Now here on this yellow path, this one did much better, and why was that? Well it's because these paths were on overcast days, and so there was no input to make sense of. Whereas on this path was on a very sunny day, and so even though the hiker couldn't see farther than a few feet in front of him, he could see shadows and say, "As long as I keep the shadows pointing in the right direction then I can go in a relatively straight line."

So the moral is we need some feedback from the environment. We can't just plan ahead and come up with a whole plan. We've got to interleave planning and executing.