lab_tic_tac_toe/nim/game.py

50 lines
2.1 KiB
Python

class NimGame:
"""A Nim game class based off NimGameStub.
"""
def get_initial_state(self):
''' Constructs the game board and has player 1 start the game. '''
return {
"board": [1, 3, 5, 7],
"first_player": True
}
def get_next_state(self, state, action):
''' Creates a copy of the current board and then makes adjustments
based on the chosen action from a player's turn. '''
new_board = state["board"].copy()
new_board[action[0]] = new_board[action[0]] - action[1]
return {
"board": new_board,
"first_player": not state["first_player"],
}
def get_actions(self, state):
''' Construct the list of actions that can be taken by a player.
Is there a more efficient way of doign this? '''
actions = []
new_board = state["board"].copy()
for i in range(4): # check the four rows of the board
if new_board[i] > 0: # if a row is not empty
for j in range(1,4): # check if you can remove 1, 2, or 3 ticks in the row
if j <= new_board[i]: # if so
actions.append((i,j)) # include that as an option
return actions
def get_reward(self, state):
''' Reports who wins. '''
if state["first_player"]:
return 1 # If it is the player's turn and there is nothing on the board, then it was the robot who crossed off the last line.
return 0 # Otherwise, the first player made the last move and lost.
def is_over(self, state):
''' Reports true if there are no more lines to cross. '''
if all(ticks == 0 for ticks in state["board"]):
return True
return False
def get_objective(self, state):
''' Reports the desired obejctive to help choose the move that
yields the optimal reward under the lookahead_strategy for
computer players. '''
return max if state["first_player"] else min