Hello, people!
You must be very busy right now, so I'll just wait until you come back in the next line.
I bet you're reading this line less then 3 seconds after you read the last one. Ha. I won. Or no.
So, today I'm going to tell some things I know about predicting events, and you may get confused or crazy. Just be aware of that fact. Oh, and what I say may not be accurate or it could be wrong, but that's the way I do it. If you have another way of thinking, tell me.
The first thing is the 'question' you make when you want to know about something in the future, like "what will happen if I don't go to work today?". With this question at hand, now we need to know about the current state, like "I'm at home, today isn't a holiday, my boss don't like people getting late to work", things like that. I call this part 'information'. It's when we gather what we know that could influence the outcome of an action, in this case going (or not) to work.
After that, comes the most complicated phase, the outcome. In a simple way, it could be "I'll get fired", and that would be just fine, you would go to work and that's it.
BUT. Let's make things complicated: you call your boss and give him a excuse. Let's call this "branch-one". So, we can divide this branch in three others, one with a lame excuse, one with a good excuse, and another with a perfect excuse. In the first, your boss don't believes you (and maybe no one would), so he still fires you. The second, he may confirm with another source about your excuse (expanding this branch, but whatever) and eventually deciding between firing you or no. The third is perfect (that means it may not exist at all), so he'll accept that and there's no problem.
And that I named 'branches', like the ones from trees, but in a abstract way. Every branch requires additional information about the current state, and maybe some info you don't have, making it not too accurate. But the main problems with branches are the additional branches, which appears when you want to take the prediction beyond.
That obviously take some time to think about, and that's when the 'time' variable comes in. In the go or not to work case, let's say you have 30 minutes to think about it. But let's say you are in a forest running from a tiger (when I wrote 'bear', I got a dejá vù, but let's keep that to another day) and you notice there's a child lost while you're running. So, the question: what you'll do? Run? Save the kid? Fight the bear? Surely you won't be able to think about all the results, so you take the best one and make it work out. It changes from person to person, but I would get the kid and continue to run like hell.
Hmmm... guess I covered a lot about predictions. So, just to fixate: first, comes the question (or question, it could be more than one, but that raises the complexity) and how much time you have to spend wondering about it. To actually predict about it, you need info and do the prediction in fact, calculating the results. However, there may be more than one possible result, and the branches enters in scene (each branch requiring more info and eventually adding more branches).
Thought that was all? Of course it's not. There's many more stuff to take into the calculation, but the most important what I call 'noise'. It's about occasional or random things that happens and you can't really predict completely, like an alien appearing in front of you (come on, it could happen). The effect is that we must calculate every one of them (impossible, just get the most likely) and create predictions that avoid or prevent that. This part gets kinda disturbing after some time, you can even go crazy after some time wondering about what could happen.
So, that's it for now. Maybe I'll write something else about this another time, but you won't need this. Forget this and be happy for it. Don't do like me and get crazy.
If you don't really care about your sanity, feel free to lose your mind. See you next time.