I've been reading material on rangevoting.org for a couple years now, and recently was discussing voting strategy with a friend. He has always voted independently, finding some extremely obscure candidate for US senate and presidential elections that he actually liked and agreed with. I have always preferred choosing between front-runners instead. So I think my friend is an honest voter, and I'm strategic. We argue on occasion but...
Simulation results from IEVS show that when the electorate is predominantly honest, the best results are achieved. This appears to hold true for each election method reported on.
This did not make sense to me intuitively. So I tried running my own simulations. My results strongly prefer strategic voters under the plurality method. One set of results that's not atypical is:
Pl regret : avg 0.349 36.550% non-zero 0.956 mean-non-zero
SPl regret : avg 0.157 24.600% non-zero 0.640 mean-non-zero
R10 regret : avg 0.059 15.600% non-zero 0.375 mean-non-zero
SR10 regret : avg 0.096 20.500% non-zero 0.470 mean-non-zero
App regret : avg 0.096 22.350% non-zero 0.429 mean-non-zero
SApp regret : avg 0.085 19.350% non-zero 0.441 mean-non-zero
IRV regret : avg 0.129 22.400% non-zero 0.576 mean-non-zero
Pl is plurality, R10 is range with 10 steps, App is approval voting, and IRV is ... well just that. I have not yet implemented a Condorcet or Borda algorithm. You can see that I'm getting much more optimistic results from strategic voters. I have no strategy for IRV voting coded up. One in mind but it should not affect results much.
My results should be treated with great suspicion. I'm taking the opportunity to learn Rust at the same time, which I'm still getting used to. My code is on github. I should really re-write this in a more accessible language like Python.
My version of "strategic voter" is, currently, to use the two top candidates in the honest election of the same type. For Plurality, vote for the best of those two. For Range, score the favorite of those as a "10" and the other as a "1". Other candidates get scored with the same scaling -- mostly 10s and 1s but with the possibility of scores in between.