Theory of Algorithms is a conceptual framework for solving a range of problems: from everyday matters, to corporate challenges, to worldwide difficulties. Once finished, this framework will help us solve all problems we face and know everything there is. The Core Algorithm is the practical applications model. Theory of Algorithms is a work-in-progress, and this blog is my introduction of its seminal concepts.
Imagine where you want to be someday. Now, how did you get there? Retrograde analysis is a style of problem solving where you work backwards from the endgame you want. It can help you win at chess -- or solve a problem in real life.
(a) We can work through a problem or situation backward, in order to solve it. For example, as Maurice Ashley suggests, reading a sentence backward can help us spot mistakes. Or (b) we can begin with the end in mind, such as visualizing a future where we've actually achieved a goal, then working backward to where we are in the present, so as to map out the pathways to realizing that vision. The TED-Ed description is (b), while Ashley's talk is more focused on (a).
Perhaps, as with many things we do, the positive effects aren't so linear: For example, playing Tetris can certainly help reduce symptoms of Post-Traumatic Stress Disorder, like flashbacks, but playing it excessively may be counter-effective.
There are structural differences in the brain for men and women, but in general both are the same functionally. The differences seem more to do with social-psychological-cultural influences.
How objects move and how sounds intensify tell our brain whether there is a threat, and they may alter our perception and experience of time as a consequence.
What we already know, what we've already learned, what we remember in any given moment are all critical, when we have to make complex, split-second decisions.
