Example #1
0
 def _get_move(self, board):
     # return a possible turn. These are a set of moves.
     return random.choice(board.get_possible_turns())
Example #2
0
                        'won':n.won,'lost':n.lost, 'draw':n.draw,})

print "\n\nturn\tprobability\twon\tWon_p\tlost\tlost_p\tdrawn\tdrawn_p"
for n in neuron_list:
    total = float(n['won']) + float(n['lost']) + float(n['draw'])
    won_p = round(n['won']/total * 100,2)
    lost_p = round(n['lost']/total * 100,2)
    drawn_p = round(n['draw']/total * 100,2)
    print "%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % (n['turn'], n['probability'], n['won'], won_p, n['lost'], lost_p, n['draw'], drawn_p)

second_level_neurons = []

print "\nBest Counter Moves!"
for prev_turn in second_level:
    board = second_level[prev_turn]
    for turn in board.get_possible_turns():
        tmp_board = board.move(turn)
        binary = s.as_binary(tmp_board)
        n,created = Neuron.objects.get_or_create(binary=binary)
        second_level_neurons.append({'turn':turn,'prev_turn':prev_turn,'binary':binary, 'probability':round(n.probability,7),
                            'won':n.won,'lost':n.lost, 'draw':n.draw,})

second_level_neurons = sorted(second_level_neurons, key=lambda x:-x['probability'])
second_level_neurons = sorted(second_level_neurons, key=lambda x:str(x['prev_turn']))

print "\n\nturn\tprobability\twon\tWon_p\tlost\tlost_p\tdrawn\tdrawn_p"
for n in second_level_neurons:
    total = float(n['won']) + float(n['lost']) + float(n['draw'])
    won_p = round(n['won']/total * 100,2)
    lost_p = round(n['lost']/total * 100,2)
    drawn_p = round(n['draw']/total * 100,2)
Example #3
0
print "\n\nturn\tprobability\twon\tWon_p\tlost\tlost_p\tdrawn\tdrawn_p"
for n in neuron_list:
    total = float(n['won']) + float(n['lost']) + float(n['draw'])
    won_p = round(n['won'] / total * 100, 2)
    lost_p = round(n['lost'] / total * 100, 2)
    drawn_p = round(n['draw'] / total * 100, 2)
    print "%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s" % (n['turn'], n['probability'],
                                              n['won'], won_p, n['lost'],
                                              lost_p, n['draw'], drawn_p)

second_level_neurons = []

print "\nBest Counter Moves!"
for prev_turn in second_level:
    board = second_level[prev_turn]
    for turn in board.get_possible_turns():
        tmp_board = board.move(turn)
        binary = s.as_binary(tmp_board)
        n, created = Neuron.objects.get_or_create(binary=binary)
        second_level_neurons.append({
            'turn': turn,
            'prev_turn': prev_turn,
            'binary': binary,
            'probability': round(n.probability, 7),
            'won': n.won,
            'lost': n.lost,
            'draw': n.draw,
        })

second_level_neurons = sorted(second_level_neurons,
                              key=lambda x: -x['probability'])