mirror of
https://github.com/BlackLight/nash.git
synced 2024-12-26 09:15:11 +01:00
A small application that simulates the behaviour of a population in an environment in which each individual can adopt between two strategies (cooperating or being in competition)
environment | ||
main.cpp | ||
Makefile | ||
nash.cpp | ||
nash.h | ||
README |
This is a small software that simulates the behaviour of a set of individuals placed (for sake of simplicity) over a matrix where each individual can choose between two strategies: - Being cooperative with the other individuals - Being in competition with the other individuals From a certain starting point, in which each individuals has its own strategy independantly from the one chosen by the others, the algorithm goes on, and a certain individual x changes its strategy if there is a neighbour having a different strategy and a higher "gain" value (i.e. that strategy takes more benefit). The algorithm is repeated as long as an equilibrium point is reached (Nash's equilibrium) in which no individual will change its strategy anymore as no change is convenient anymore. This balance point won't be always reached anyway, and the algorithm recognizes a scenario that has no Nash's equilibrium point when a loop occurs (i.e. when it takes in exam a configuration that was already met). Usage of the program: compile simply issuing `make', then start it with ./nash <environment_file> <coop_coop_gain> <coop_comp_gain> <comp_coop_gain> <comp_comp_gain> where - environment_file is a file containing the starting configuration of the environment (an example is included in the file `environment'). In this file the collaborating individuals are marked by a dot `.', and the ones in competition are marked by a `X'. Starting from here you can easily create your environment file; - coop_coop_gain: Score gained when the individual x cooperates and its neighbour cooperates as well; - coop_comp_gain: Score gained when the individual x cooperates and its neighbour is in competition; - comp_coop_gain: Score gained when the individual x is in competition and its neighbour cooperates; - comp_comp_gain: Score gained when both the individual x and its neighbour are in competition. An example is the problem of the two prisoners: - When A doesn't confess and B doesn't confess too, they both get 8 years of prison (coop_coop_gain = -8); - When A doesn't confess and B confesses, A gets 20 years of prison and B is free (coop_comp_gain = -20); - When A confesses and B doesn't, A is free and B gets 20 years of prison (comp_coop_gain = 0); - When both A and B confess, they both get 14 years of prison (comp_comp_gain = -14). For running a simulation of the two prisoners' problem over the example environment just type ./nash environment -8 -20 0 -14 Have fun.