Exemplo n.º 1
0
    def selection(self, tournament_count=0):

        if tournament_count > self.MAX_POPULATION:
            raise ImproperlyConfiguredError, "Tournament size is bigger than population"

        def get_random(count):
            play_off = []
            for i in xrange(0, count):
                selected = random.choice(self.population)
                while selected in play_off:
                    selected = random.choice(self.population)
                play_off.append(selected)
            return play_off

        if tournament_count <= 2:
            play_off = get_random(2)
            return play_off[0], play_off[1]

        if tournament_count == self.MAX_POPULATION:
            play_off = self.population[:]
        else:
            play_off = get_random(tournament_count)

        mt = tournament.MancalaTournament(play_off)
        mt.run()

        return mt.score_board()[:2]
Exemplo n.º 2
0
    def fitness(self):

        for cro in self.population:
            cro.won = []
            cro.lost = []
            cro.drawn = []

        print "Population is: %s " % len(self.population)

        mt = tournament.MancalaTournament(self.population)
        mt.run()
        sb = mt.score_board(method='difference', second='football')
        self.population_fitness = sb
        return sb
Exemplo n.º 3
0
        def crossover(parent1, parent2):
            #  a b c d e f g
            #  A B C D E F G
            # =a b c D E F G
            weight_keys = parent1.weights.keys()
            length = len(weight_keys)

            childa = engine.players.ConfiguredPlayer(
                parent1.player_class,
                settings=parent1.settings,
                skip_validation=True,
            )
            childb = engine.players.ConfiguredPlayer(
                parent1.player_class,
                settings=parent2.settings,
                skip_validation=True,
            )

            for i in xrange(0, length):
                weight_name = weight_keys[i]
                p1_weight = parent1.weights[weight_name]
                p2_weight = parent2.weights[weight_name]
                if i <= (length / 2):
                    childa.weights[weight_name] = p1_weight
                    childb.weights[weight_name] = p2_weight
                else:
                    childa.weights[weight_name] = p2_weight
                    childb.weights[weight_name] = p1_weight

            play_off = [
                childa,
                childb,
            ]
            if parents_can_survive:
                play_off = [
                    childa,
                    childb,
                    parent1,
                    parent2,
                ]

            mt = tournament.MancalaTournament(play_off)
            mt.run()
            return mt.winner()
Exemplo n.º 4
0
    def test_score_board(self):
        """ Run through an example tournament and check the score board 
        creation is working properly.
        
        """

        PLAYER_LIST = []

        for i in range(0, 5):
            cp = ConfiguredPlayer(
                basic.RandomPlayer,
                name="R%s" % i,
            )
            PLAYER_LIST.append(cp, )

        mt = tournament.MancalaTournament(PLAYER_LIST)
        mt.run()
        # TODO: Think of a test to validate the score_board result.
        #    Always different so its hard... The only test could really
        #    check the order but thats more testing the python sort
        # built in than anything else...
        sb = mt.score_board()
Exemplo n.º 5
0
        def meet(parent1, parent2):
            #  8 6 2 4 8 0 9
            #  2 6 6 4 0 4 7
            # =6 6 4 4 4 2 8
            weight_keys = parent1.weights.keys()
            length = len(weight_keys)
            child = engine.players.ConfiguredPlayer(
                parent1.player_class,
                settings=parent1.settings,
                skip_validation=True,
            )

            for i in xrange(0, length):
                weight_name = weight_keys[i]
                p1_weight = parent1.weights[weight_name]
                p2_weight = parent2.weights[weight_name]
                if not weight_name.endswith('_multi'):
                    meet_val = (p1_weight + p2_weight) / 2
                    child.weights[weight_name] = meet_val
                else:
                    new_multi = []

                    for j in xrange(0, len(p1_weight)):
                        new_multi.append((p1_weight[j] + p2_weight[j]) / 2)

                    child.weights[weight_name] = new_multi

            if parents_can_survive:
                play_off = [
                    child,
                    parent1,
                    parent2,
                ]
                mt = tournament.MancalaTournament(play_off)
                mt.run()
                return mt.winner()
            else:
                return child
Exemplo n.º 6
0
 def test_minimax_depth(self):
     """ A tournament of minimax players with the same weights but 
     different depths - should give a fairly good test as to how the 
     depth of the search tree effects the result.
     
     """
     
     number_of_each = 1
     max_depth = 4
     
     PLAYER_LIST = []
     
     random_bases = []
     for x in xrange(0,number_of_each):
         random_bases.append(basic.MiniMaxPlayer.objects.random(name="M2%s" %x, settings={'max_depth':1,}))
         random_bases.append(basic.MiniMaxPlayer.objects.random(name="M2%s" %x, settings={'max_depth':1,}))
     
     for y in xrange(1,max_depth+1):
         for i in xrange(0,number_of_each):
             PLAYER_LIST.append(basic.MiniMaxPlayer.objects.random(name="M%s%s" %(y,i), weights=random_bases[i].weights, settings={'max_depth':y,}))
     
     mt = tournament.MancalaTournament(PLAYER_LIST)
     mt.run()
     sb = mt.score_board()
Exemplo n.º 7
0
    'max_depth': 3,
}
weights = weights = {
    'scrape': 100.0,
    'store': 10.0,
    'score': 0.5,
    'stance': 0.0,
    'pits_multi': [10.0, 9.0, 8.0, 7.0, 6.0, 5.0],
}
cro = players.ConfiguredPlayer(basic.MiniMaxPlayer,
                               weights,
                               settings=settings,
                               name="MMCC")
player_list.append(cro)

t = tournament.MancalaTournament(player_list)

r = t.run(yield_length=True)

l = list(r)

print sum([len(i) for i in l]) / len(l)
print max([len(i) for i in l])
print min([len(i) for i in l])

games = l[0]

for game in games:
    print game.board
    import time
    time.sleep(10)
Exemplo n.º 8
0
    random_bases.append(
        basic.MiniMaxPlayer.objects.random(name="M2%s" % x,
                                           settings={
                                               'max_depth': 1,
                                           }))

for i in range(100):
    r = players.ConfiguredPlayer(
        basic.RandomPlayer,
        name="R %s" % i,
    )
    PLAYER_LIST.append(r)

for y in range(1, max_depth + 1):
    for i in range(0, number_of_each):
        mm = basic.MiniMaxPlayer.objects.random(
            name="M%s%s" % (y, i),
            weights=random_bases[i].weights,
            settings={
                'max_depth': y,
            })
        PLAYER_LIST.append(mm)

mt = tournament.MancalaTournament(PLAYER_LIST)
mt.VERBOSE = True
mt.run()
sb = mt.score_board()

for c in sb:
    print c