jensandClaude Sonnet 5
455ea692f5
Uses argparse.BooleanOptionalAction so these behave like --verbose (e.g. "--human" instead of "--human True"), while keeping their current defaults (False, False, True) and adding --no-train/--no-human/ --no-load counterparts. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PQS7ZHqxQfy5DhKcz2gHau
109 lines
3.2 KiB
Python
109 lines
3.2 KiB
Python
import numpy as np
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from state import create_empty_state, to_state_string
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from machine_player import MachinePlayer
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from human_player import HumanPlayer
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from player_provider import PlayerProvider
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import json
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import argparse
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float_formatter = "{:.3f}".format
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np.set_printoptions(formatter={'float_kind': float_formatter})
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REPORT_INTERVAL = 1000
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report_counter = REPORT_INTERVAL
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def play(player_provider: PlayerProvider, k_max=10000, with_debug=False):
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player_provider.set_debug(with_debug)
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for k in range(0, k_max):
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state = create_empty_state()
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players = player_provider.choose(state)
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move = 1
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run = True
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other_player = players[-1]
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while run:
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do_stop = False
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this_reward = 0
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other_reward = 0
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for this_player in players:
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if with_debug:
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print(f"---------------------------------------------------")
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print(f"- Game {k:06d}, Move {move} -----------------------------")
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print(f"---------------------------------------------------")
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last_state = state
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state, has_moved = this_player.move(state)
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if with_debug:
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print(to_state_string(last_state, state))
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if not has_moved:
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this_reward = 0
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other_reward = 0
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do_stop = True
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if with_debug:
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print(f"{this_player.mark}: No more moves")
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if this_player.has_won(state):
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this_reward = 1
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other_reward = 0
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do_stop = True
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if with_debug:
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print(f"{this_player.mark}: Has won the game")
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if do_stop:
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this_player.end_game(state, this_reward)
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other_player.end_game(state, other_reward)
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run = False
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break
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other_player = this_player
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move += 1
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument("--verbose", default=False, action='store_true', help="Be verbose")
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parser.add_argument("--train", default=False, action=argparse.BooleanOptionalAction, help="Train before play")
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parser.add_argument("--num", default=5, type=int, help="Number of games to play")
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parser.add_argument("--human", default=False, action=argparse.BooleanOptionalAction, help="X-player is human")
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parser.add_argument("--load", default=True, action=argparse.BooleanOptionalAction, help="Load experience from previous trainings")
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args = parser.parse_args()
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if args.load:
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try:
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with open("values_x.json", "r") as fp:
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x_values = json.load(fp)
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with open("values_o.json", "r") as fp:
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o_values = json.load(fp)
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except Exception:
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x_values = {}
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o_values = {}
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else:
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x_values = {}
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o_values = {}
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p_mx = MachinePlayer(mark='X', params=MachinePlayer.Params(p_explore=0.1, alpha=0.1), values=x_values)
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p_mo = MachinePlayer(mark='O', params=MachinePlayer.Params(p_explore=0.1, alpha=0.1), values=o_values)
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N = args.num
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if args.train:
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for n in range(0, N):
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play(PlayerProvider(p_mx, p_mo), 1000, False)
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# Values after training
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# Convert and write JSON object to file
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with open("values_x.json", "w") as fp:
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json.dump(p_mx.values, fp, indent=0)
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with open("values_o.json", "w") as fp:
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json.dump(p_mo.values, fp, indent=0)
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print(f"Iteration: {n*N:8d}")
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if args.human:
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p_hx = HumanPlayer(mark='X', name="Jens")
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pp = PlayerProvider(p_hx, p_mo)
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else:
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pp = PlayerProvider(p_mx, p_mo)
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play(pp, N, args.verbose)
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