(My) ideal society

Each individual is respected as such and has the freedom and the means to pursue its own interests without having to harm the others.

Don’t know how it looks like. It’s a pretty simple (non-constructive) definition, however.
I’m sure mathematicians like it! LOL

Personal productivity, happiness and optimization algorithms

I spend lots of time wondering about the best ways to be both more productive and happy. Curiously, I’m coming to the conclusion that this is exactly what I should not do.

Being productive, like being happy, requires living the present moment, not thinking about it.

If you want to complete a task, the best strategy is just doing it! You might start by setting up a plan, a sequence of smaller actions that lead you to your goal, but once you have this, just do it. Spending too much energy re-planning and judging yourself along the way is just counter-productive.

Curiously, this is not easy! Our brain seems to have some bad habits hard-wired. Want it or not, we start thinking about the past or making predictions about the future. Worse, we start multi-tasking (as you read this blog, you might also be listening to music, doing some work, or chatting with your friends in facebook)
Perhaps the only solution is to re-train our neuron connections. One way to do it would be meditating or repeatedly performing a task that requires one to be focused on the present. Feeling, not thinking. After enough practicing, the brain should start rewiring.

I recently came across this famous Hemingway sentence:

“Happiness in intelligent people is the rarest thing I know.”

Perhaps intelligent people have the tendency to plan too much? Planning involves predicting the reward associated with a set of possible actions and choosing the best ones. What if the reward function is not easily predictable? Perhaps the best optimization algorithm in this case is a greedy one. Don’t plan to be happy only next year or next month or even tomorrow. You are dealing with a real-time multi-agent system, you have only partial and noisy data about the world, the system is recursive, and finding the optimal reward is probably NP-hard-as-it-can-be!