Example #1
0
        continue

    rgb = [int(x) for x in entry[1:4]]
    word = entry[4][:-1]
    learnerB.learn(word, Expression(["COLOUR", "r_%d" % rgb[0],
                                         "g_%d" % rgb[1],
                                         "b_%d" % rgb[2] ]))


# pick sample of N random colours
test_colours = [
    (random.randint(0,255), 
     random.randint(0,255), 
     random.randint(0,255)) for i in range(args.num_test_samples)]

logger.log_points("langA", test_colours)
logger.mean("langA")

# generation simulation
for generation in range(1,args.generations):
    learnerA = learnerB
    learnerB = gauss_colour.GaussianColourSemantics("L_%d" % generation, creative=True)

    logger.learner = learnerB
    
    # train L(i+1) (B) from L(i) (A)
    for i in range(0, args.num_train_samples):
        (word, meaning) = learnerA.say_something()
        learnerB.learn(word, meaning)

    # output sample from trained L(i+1)
Example #2
0
logger = logger.colour_logger.ColourLogger(learnerA)

# train A from stdin
for line in fileinput.input():
    entry = line.split(",")

    if entry[0] == "lang.name":
        continue

    rgb = [int(x) for x in entry[1:4]]
    word = entry[4][:-1]
    learnerA.learn(word, pack_expression(rgb))

# pick sample of N random colours (in blue subspace)
test_colours = [pick_random_blue() for i in range(NUM_SAMPLES)]

# output for learner A
logger.log_points("langA", test_colours)

logger.learner = learnerB

# iteratively train learner B on A's utterances (N iterations)
for i in range(0, TRAINING_ITERATIONS):
    meaning = pack_expression(pick_random_blue())

    word = learnerA.word_for(meaning)
    learnerB.learn(word, meaning)

    if i % SKIP == 0:
        logger.log_points("langB_%02d" % i, test_colours)