def team_test(load=False):
game = Game(100, 100)
agent1 = Agent()
agent1b = Agent()
agent2 = QLearningAgent(epsilon=0.5, alpha=.2, alpha_decay=1.0)
agent2b = QLearningAgent(epsilon=0.5, alpha=.2, alpha_decay=1.0)
if load:
agent2.load_weights("team_weights.txt")
agent2.alpha = 0
# add agents
game.add_agent(agent1, (47, 30), 0)
game.add_agent(agent1b, (53, 30), 0)
game.add_agent(agent2, (0, 0), 1)
game.add_agent(agent2b, (0, 50), 1)
# simulate game
iterations = 10000
atexit.register(lambda: agent2.save_weights("team_weights.txt"))
game.start()
# agent2.debug = True
if not load: run_for_iterations(game, iterations)
game.add_listener(GraphicsListener(game))
agent2.epsilon = 0.01
agent2b.epsilon = 0.01
for _ in xrange(iterations):
game.loop()
time.sleep(.05)
def single_agent_test(load=False):
game = Game(100, 100)
agent = QLearningAgent(alpha=.2, alpha_decay=1.0, epsilon=.5)
if load:
agent.load_weights("single_agent_weights.txt")
agent.alpha = 0
agent.epsilon = .01
# add agents
game.add_agent(agent, (25, 15), 0)
# simulate game
iterations = 50000
atexit.register(lambda: agent.save_weights("single_agent_weights.txt"))
game.start()
# agent.debug = True
if not load: run_for_iterations(game, 10000)
game.add_listener(GraphicsListener(game))
for _ in xrange(iterations):
game.loop()
time.sleep(.05)