def main():
bots = [MyBot()]
bots.extend(other_bots.get_bots(5, 2))
# Plot a single run. Useful for debugging and visualizing your
# bot's performance. Also prints the bot's final profit, but this
# will be very noisy.
#plot_simulation.run(bots, lmsr_b=250)
# Calculate statistics over many runs. Provides the mean and
# standard deviation of your bot's profit.
run_experiments.run(bots, simulations=1000, lmsr_b=250)
def main():
bots = [MyBot()]
bots.extend(other_bots.get_bots(5, 2))
# Plot a single run. Useful for debugging and visualizing your
# bot's performance. Also prints the bot's final profit, but this
# will be very noisy.
#plot_simulation.run(bots, lmsr_b=150, timesteps=100)
# Calculate statistics over many runs. Provides the mean and
# standard deviation of your bot's profit.
run_experiments.run(bots, simulations=1000, lmsr_b=150, num_processes=2, timesteps=100)
def main():
bots = [MyBot()]
# 5,2 to start
num_fundamentals = 8
num_technical = 2
bots.extend(other_bots.get_bots(num_fundamentals, num_technical))
# Plot a single run. Useful for debugging and visualizing your
# bot's performance. Also prints the bot's final profit, but this
# will be very noisy.
plot_simulation.run(bots, lmsr_b=250)
# Calculate statistics over many runs. Provides the mean and
# standard deviation of your bot's profit.
run_experiments.run(bots, num_processes=4, simulations=1000, lmsr_b=250)
def main():
bots = [MyBot()]
fundamental = 10
technical = 1
bots.extend(other_bots.get_bots(fundamental,technical))
print ('Fundamental: {}, Technical: {}'.format(fundamental,technical))
# Plot a single run. Useful for debugging and visualizing your
# bot's performance. Also prints the bot's final profit, but this
# will be very noisy.
#plot_simulation.run(bots, 200, lmsr_b=250)
# Calculate statistics over many runs. Provides the mean and
# standard deviation of your bot's profit.
run_experiments.run(bots, num_processes=4, simulations=2000, lmsr_b=250)