def bng(seed, generations, render, show, time_limit):
l.info('Starting BeamNG.AI with seed: {}'.format(seed))
# Ensure the right configurations are there
# Force the use of BeamNG.AI
config.ex.ai_controlled = 'true'
# TODO: we should use the tool-competition framework as a runner
factory = gen_beamng_runner_factory(config.ex.get_level_dir(), config.ex.host, config.ex.port, plot=show)
# TODO: we need to consider the projection to (x,y) coordinates for the tool-competition framework
experiments.experiment(seed, generations, factory, render=render, show=show, time_limit=time_limit)
def ext(seed, generations, render, show, time_limit, ctrl):
l.info('Starting external AI {} with seed: {}'.format(ctrl, seed))
# Ensure the right confiruations are there
# Do not use super-fast-time
config.ex.max_speed = 'false'
# Do not use BeamNG.AI
config.ex.ai_controlled = 'false'
# TODO No idea what this
# config.ex.direction_agnostic_boundary = True
factory = gen_beamng_runner_factory(config.ex.get_level_dir(), config.ex.host, config.ex.port, plot=show, ctrl=ctrl)
experiments.experiment(seed, generations, factory, render=render, show=show, time_limit=time_limit)
def bng(seed, generations, render, show, time_limit):
l.info('Starting BeamNG.AI with seed: {}'.format(seed))
# Ensure the right configurations are there
# Force the use of BeamNG.AI
config.ex.ai_controlled = 'true'
factory = gen_beamng_runner_factory(config.ex.get_level_dir(),
config.ex.host,
config.ex.port,
plot=show)
experiments.experiment(seed,
generations,
factory,
render=render,
show=show,
time_limit=time_limit)
def ext(seed, generations, render, uniq, time_limit, ctrl):
l.info('Starting external evolve with seed: {}'.format(seed))
l.info('Time limit will be enforced at: {}'.format(time_limit))
l.info('AI Controller call given is: %s', ctrl)
# plots_dir = config.rg.get_plots_path()
# tests_dir = config.rg.get_tests_path()
level_dir = config.ex.get_level_dir()
# config.ev.join_probability = 1.1
# config.ev.lane_width = 4.3
# if uniq:
# config.ev.evaluator = 'uniqlanedist'
# else:
# config.ev.evaluator = 'lanedist'
# config.ev.try_all_ops = False
config.ex.max_speed = 'false'
config.ex.ai_controlled = 'false'
config.ex.direction_agnostic_boundary = True
rng = random.Random()
rng.seed(seed)
factory = gen_beamng_runner_factory(level_dir,
config.ex.host,
config.ex.port,
False,
ctrl=ctrl)
# evaluator = LaneDistanceEvaluator()
# selector = TournamentSelector(rng, 2)
# estimator = TurnAndLengthEstimator()
# experiments.experiment_out(rng, evaluator, selector, estimator, factory,
# True, generations, render=render)
budget = generations
experiments.experiment(seed,
budget,
time_limit=time_limit,
render=render,
show=False,
factory=factory)
def bng(seed, budget, render, show):
l.info('Starting experiment with seed: %s', seed)
l.info('Starting experiment with budget: %s', budget)
experiments.experiment(seed, budget, render, show)