def _breed_new_ai(self, cursor, old_player_ids):
"""Breed a new AI, from two weighted-random experienced parents."""
query = """SELECT p.player_id, p.mu FROM player p
WHERE p.class = 'CleverBot'"""
cursor.execute(query)
rows = cursor.fetchall()
possible_parents = []
for row in rows:
mu = row["mu"]
player_id = row["player_id"]
if player_id in old_player_ids:
possible_parents.append((mu, player_id))
tup1 = Dice.weighted_random_choice(possible_parents)
possible_parents.remove(tup1)
tup2 = Dice.weighted_random_choice(possible_parents)
player_id1 = tup1[1]
info1 = self.get_player_info(player_id1)
bp1 = BotParams.BotParams.fromstring(info1)
player_id2 = tup2[1]
info2 = self.get_player_info(player_id2)
bp2 = BotParams.BotParams.fromstring(info2)
bp3 = bp1.cross(bp2).mutate_random_field()
bot = CleverBot.CleverBot("child", config.DEFAULT_AI_TIME_LIMIT, bp3)
info = bot.player_info
logging.info("player_info %s", info)
query = """INSERT INTO player (class, info, mu, sigma)
VALUES (?, ?, ?, ?)"""
cursor.execute(query, ("CleverBot", info, DEFAULT_MU, DEFAULT_SIGMA))
# And fetch the player_id.
query = """SELECT player_id FROM player
where class = ? AND info = ?"""
cursor.execute(query, ("CleverBot", info))
row = cursor.fetchone()
player_id = row["player_id"]
# And update the name.
name = "ai%d" % player_id
query = """UPDATE player SET name = ?
WHERE player_id = ?"""
cursor.execute(query, (name, player_id))
logging.info("father %s %s", player_id1, bp1)
logging.info("mother %s %s", player_id2, bp2)
logging.info("baby %s %s %s", player_id, name, bp3)
return player_id
def _breed_new_ai(self, cursor, old_player_ids):
"""Breed a new AI, from two weighted-random experienced parents."""
query = """SELECT p.player_id, p.mu FROM player p
WHERE p.class = 'CleverBot'"""
cursor.execute(query)
rows = cursor.fetchall()
possible_parents = []
for row in rows:
mu = row["mu"]
player_id = row["player_id"]
if player_id in old_player_ids:
possible_parents.append((mu, player_id))
tup1 = Dice.weighted_random_choice(possible_parents)
possible_parents.remove(tup1)
tup2 = Dice.weighted_random_choice(possible_parents)
player_id1 = tup1[1]
info1 = self.get_player_info(player_id1)
bp1 = BotParams.BotParams.fromstring(info1)
player_id2 = tup2[1]
info2 = self.get_player_info(player_id2)
bp2 = BotParams.BotParams.fromstring(info2)
bp3 = bp1.cross(bp2).mutate_random_field()
bot = CleverBot.CleverBot("child", config.DEFAULT_AI_TIME_LIMIT, bp3)
info = bot.player_info
logging.info("player_info %s", info)
query = """INSERT INTO player (class, info, mu, sigma)
VALUES (?, ?, ?, ?)"""
cursor.execute(query, ("CleverBot", info, DEFAULT_MU, DEFAULT_SIGMA))
# And fetch the player_id.
query = """SELECT player_id FROM player
where class = ? AND info = ?"""
cursor.execute(query, ("CleverBot", info))
row = cursor.fetchone()
player_id = row["player_id"]
# And update the name.
name = "ai%d" % player_id
query = """UPDATE player SET name = ?
WHERE player_id = ?"""
cursor.execute(query, (name, player_id))
logging.info("father %s %s", player_id1, bp1)
logging.info("mother %s %s", player_id2, bp2)
logging.info("baby %s %s %s", player_id, name, bp3)
return player_id
def test_weighted_random_choice(self):
lst = [
(0.4, 1),
(0.3, 2),
(0.2, 3),
(0.1, 4),
]
# Can use a Counter when we require Python 2.7
counter = defaultdict(int)
for trial in xrange(1000):
tup = Dice.weighted_random_choice(lst)
print tup
counter[tup[1]] += 1
print counter
assert sum(counter.itervalues()) == 1000
assert counter[1] > counter[2] > counter[3] > counter[4]
def test_weighted_random_choice(self):
lst = [
(0.4, 1),
(0.3, 2),
(0.2, 3),
(0.1, 4),
]
# Can use a Counter when we require Python 2.7
counter = defaultdict(int)
for trial in xrange(1000):
tup = Dice.weighted_random_choice(lst)
print tup
counter[tup[1]] += 1
print counter
assert sum(counter.itervalues()) == 1000
assert counter[1] > counter[2] > counter[3] > counter[4]
def get_weighted_random_player_id(self, excludes=(), highest_mu=False):
"""Return a player_id. Exclude any player_ids in excludes.
If there are fewer than GENERATION_SIZE AI player_id in the database,
add a new AI (by mutating the default) and return its player_id.
If highest_mu is not None, then return the eligible player_id with
the highest mu.
If there are fewer than GENERATION_SIZE AI player_ids in the database
with sigma <= BREEDING_SIGMA_THRESHOLD, breed a new AI (by
crossing two parent AIs with sigma <= BREEDING_SIGMA_THRESHOLD,
chosen randomly weighted by mu), and return its player_id.
Otherwise, choose an existing player_id randomly, weighted by low
sigma, and return it.
"""
with self.connection:
cursor = self.connection.cursor()
total_ai_count = 0
query = """SELECT player_id, mu, sigma FROM player p
WHERE p.class='CleverBot'"""
cursor.execute(query)
rows = cursor.fetchall()
young_player_ids = set()
old_player_ids = set()
for row in rows:
player_id = row["player_id"]
sigma = row["sigma"]
if sigma <= BREEDING_SIGMA_THRESHOLD:
old_player_ids.add(player_id)
else:
young_player_ids.add(player_id)
young_ai_count = len(young_player_ids)
old_ai_count = len(old_player_ids)
total_ai_count = young_ai_count + old_ai_count
if highest_mu:
# Pick the eligible AI with the highest mu and return its
# player_id.
query = """SELECT player_id, mu FROM player
WHERE class = 'CleverBot'
ORDER BY mu DESC"""
cursor.execute(query)
rows = cursor.fetchall()
for row in rows:
player_id = row["player_id"]
if player_id not in excludes:
logging.info("picked high-mu AI %s", player_id)
return player_id
if young_ai_count < GENERATION_SIZE and old_ai_count >= 2:
# Not enough young AIs, so breed one.
return self._breed_new_ai(cursor, old_player_ids)
else:
candidates = []
# Pick an existing young AI randomly, weighted by low sigma,
# and return its player_id.
query = """SELECT player_id, sigma FROM player
WHERE class = 'CleverBot'"""
cursor.execute(query)
rows = cursor.fetchall()
for row in rows:
player_id = row["player_id"]
sigma = row["sigma"]
if player_id in young_player_ids and player_id not in excludes:
candidates.append((1.0 / sigma, player_id))
if candidates:
tup = Dice.weighted_random_choice(candidates)
player_id = tup[1]
logging.info("picked random AI %s", player_id)
return player_id
else:
# No eligible AIs available, so either breed or spawn
# a new one.
if total_ai_count < GENERATION_SIZE:
return self._spawn_new_ai(cursor)
elif old_ai_count >= 2:
return self._breed_new_ai(cursor, old_player_ids)
else:
return self._spawn_new_ai(cursor)
def get_weighted_random_player_id(self, excludes=(), highest_mu=False):
"""Return a player_id. Exclude any player_ids in excludes.
If there are fewer than GENERATION_SIZE AI player_id in the database,
add a new AI (by mutating the default) and return its player_id.
If highest_mu is not None, then return the eligible player_id with
the highest mu.
If there are fewer than GENERATION_SIZE AI player_ids in the database
with sigma <= BREEDING_SIGMA_THRESHOLD, breed a new AI (by
crossing two parent AIs with sigma <= BREEDING_SIGMA_THRESHOLD,
chosen randomly weighted by mu), and return its player_id.
Otherwise, choose an existing player_id randomly, weighted by low
sigma, and return it.
"""
with self.connection:
cursor = self.connection.cursor()
total_ai_count = 0
query = """SELECT player_id, mu, sigma FROM player p
WHERE p.class='CleverBot'"""
cursor.execute(query)
rows = cursor.fetchall()
young_player_ids = set()
old_player_ids = set()
for row in rows:
player_id = row["player_id"]
sigma = row["sigma"]
if sigma <= BREEDING_SIGMA_THRESHOLD:
old_player_ids.add(player_id)
else:
young_player_ids.add(player_id)
young_ai_count = len(young_player_ids)
old_ai_count = len(old_player_ids)
total_ai_count = young_ai_count + old_ai_count
if highest_mu:
# Pick the eligible AI with the highest mu and return its
# player_id.
query = """SELECT player_id, mu FROM player
WHERE class = 'CleverBot'
ORDER BY mu DESC"""
cursor.execute(query)
rows = cursor.fetchall()
for row in rows:
player_id = row["player_id"]
if player_id not in excludes:
logging.info("picked high-mu AI %s", player_id)
return player_id
if young_ai_count < GENERATION_SIZE and old_ai_count >= 2:
# Not enough young AIs, so breed one.
return self._breed_new_ai(cursor, old_player_ids)
else:
candidates = []
# Pick an existing young AI randomly, weighted by low sigma,
# and return its player_id.
query = """SELECT player_id, sigma FROM player
WHERE class = 'CleverBot'"""
cursor.execute(query)
rows = cursor.fetchall()
for row in rows:
player_id = row["player_id"]
sigma = row["sigma"]
if (player_id in young_player_ids
and player_id not in excludes):
candidates.append((1.0 / sigma, player_id))
if candidates:
tup = Dice.weighted_random_choice(candidates)
player_id = tup[1]
logging.info("picked random AI %s", player_id)
return player_id
else:
# No eligible AIs available, so either breed or spawn
# a new one.
if total_ai_count < GENERATION_SIZE:
return self._spawn_new_ai(cursor)
elif old_ai_count >= 2:
return self._breed_new_ai(cursor, old_player_ids)
else:
return self._spawn_new_ai(cursor)
