# Setup NN
net = JasonNet()
current_NN = net
best_NN = net
if not os.path.isdir("model_data"):
os.mkdir("model_data")
logger.info("Starting to train...")
for i in range(args.iteration, args.total_iterations):
logger.info(F"Iteration {i}")
# Play a number of Episodes (games) of self play to generate data
generate_data(current_NN, episodes, search_depth, i)
# original monte carlo
#run_monte_carlo(current_NN, 0, i, episodes, search_depth)
# Train NN from dataset of monte carlo tree search above
train_net(current_NN, i, args.lr, args.bs, args.epochs)
# Fight new version against reigning champion in the Arena
# Even with first iteration just battle against yourself
arena = Arena(best_NN, current_NN)
best_NN = arena.battle(episodes // 2, search_depth)
# Save the winning net as a Pickle for battle later
save_as_pickle(i, best_NN)
print("End of the main driver program. Training has completed!")
from Arena import Arena
from IPython.display import clear_output
arena = Arena()
while True:
print('''
1. Create pokemon
2. Show Existing pokemon
3. Battle
4. Quit
''')
choice = int(input('Enter your choice:'))
if choice == 1:
arena.create_pokemon()
elif choice == 2:
arena.show_all()
pass
elif choice == 3:
clear_output()
arena.battle()
pass
else:
break
from RockBot import RockBot
from ScissorsBot import ScissorsBot
from PaperBot import PaperBot
from BeatLastBot import BeatLastBot
from RockThenPaperThenScissorsBot import RockThenPaperThenScissorsBot
from ScissorsThenPaperThenRockBot import ScissorsThenPaperThenRockBot
from Arena import Arena
if __name__ == '__main__':
rockBot = RockBot()
scissorsBot = ScissorsBot()
paperBot = PaperBot()
beatLastBot = BeatLastBot()
rockThenPaperThenScissorsBot = RockThenPaperThenScissorsBot()
scissorsThenPaperThenRockBot = ScissorsThenPaperThenRockBot()
arena = Arena()
arena.battle(beatLastBot, rockThenPaperThenScissorsBot, 20)
arena.__init__()
beatLastBot.__init__()
arena.battle(beatLastBot, scissorsThenPaperThenRockBot, 20)
