def main(args):
game, serial = gameio.read_game(json.load(args.input))
if args.type == 'pure':
equilibria = nash.pure_nash(game, args.regret)
if args.one and not equilibria:
equilibria = nash.min_regret_profile(game)[None]
elif args.type == 'mixed':
rep_args = {
'max_iters': args.max_iterations,
'converge_thresh': args.convergence
}
equilibria = nash.mixed_nash(game, args.regret, args.distance,
random_restarts=args.random_mixtures,
grid_points=args.grid_points,
at_least_one=args.one,
processes=args.processes,
replicator=rep_args, optimize={})
equilibria = game.trim_mixture_support(equilibria, args.support)
elif args.type == 'min-reg-prof':
equilibria = nash.min_regret_profile(game)[None]
elif args.type == 'min-reg-grid':
equilibria = nash.min_regret_grid_mixture(
game, args.grid_points)[None]
equilibria = game.trim_mixture_support(equilibria, args.support)
elif args.type == 'min-reg-rand':
equilibria = nash.min_regret_rand_mixture(
game, args.random_mixtures)[None]
equilibria = game.trim_mixture_support(equilibria, args.support)
elif args.type == 'rand':
equilibria = game.random_mixtures(args.random_mixtures)
equilibria = game.trim_mixture_support(equilibria, args.support)
else:
raise ValueError('Unknown command given: {0}'.format(args.type)) # pragma: no cover # noqa
json.dump([serial.to_prof_json(eqm) for eqm in equilibria], args.output)
args.output.write('\n')
def test_minreg_rand_roshambo():
game = gamegen.rock_paper_scissors()
eqm = nash.min_regret_rand_mixture(game, 20)
assert regret.mixture_regret(game, eqm) < 2 + 1e-7, \
"Found a mixture with greater than maximum regret"
