Yesterday, i spent lots of time reading on game theory and thinking of different ways to invite new games. The most cool thought experiment game I found was The Pirate Game . I really like the logic and reasoning behind the results.
Ok so what to do.. I was thinking about applying Statistical Mechanics to decision making processes and seeing how that led to self-organization or equilibrium behaviour. Simulated actions would be described by probability distribution. The problem is I keep thinking that I am just coming back to molecular dynamics.
Strategies is also an interesting part of Game Theory. As in finding optimal strategies for simple games.
I am more inclined towards the simulation part though. I just have not been able to figure out how to distill things down to a simple simulation.
Conway's Game of Life was interesting to people because it only had 4 rules even though they were completely arbitrary:
- Any live cell with fewer than two live neighbours dies, as if caused by under-population.
- Any live cell with two or three live neighbours lives on to the next generation.
- Any live cell with more than three live neighbours dies, as if by overcrowding.
- Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction.
How much randomness or stochasticity would it take to ruin a self-organized system?
What does it take for a self-organized system to stay self-organized even with X amount of noise or stochasticity?
I need more time to think and maybe more time to drink. It's Friday and almost time for graduate student seminar.
