61 lines
2.2 KiB
Python
61 lines
2.2 KiB
Python
import random
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from environments.factory.factory_battery import BatteryFactory, BatteryProperties
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from environments.factory.factory_dirt import DirtFactory, DirtProperties
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from environments.factory.factory_item import ItemFactory
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# noinspection PyAbstractClass
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class DirtItemFactory(ItemFactory, DirtFactory):
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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# noinspection PyAbstractClass
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class DirtBatteryFactory(DirtFactory, BatteryFactory):
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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if __name__ == '__main__':
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from environments.utility_classes import AgentRenderOptions as ARO, ObservationProperties
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render = True
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dirt_props = DirtProperties(1, 0.05, 0.1, 3, 1, 20, 0)
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obs_props = ObservationProperties(render_agents=ARO.COMBINED, omit_agent_self=True,
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pomdp_r=2, additional_agent_placeholder=None)
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move_props = {'allow_square_movement': True,
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'allow_diagonal_movement': False,
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'allow_no_op': False}
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factory = DirtBatteryFactory(n_agents=5, done_at_collision=False,
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level_name='rooms', max_steps=400,
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obs_prop=obs_props, parse_doors=True,
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record_episodes=True, verbose=True,
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btry_prop=BatteryProperties(),
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mv_prop=move_props, dirt_prop=dirt_props
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)
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# noinspection DuplicatedCode
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n_actions = factory.action_space.n - 1
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_ = factory.observation_space
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for epoch in range(4):
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random_actions = [[random.randint(0, n_actions) for _
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in range(factory.n_agents)] for _
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in range(factory.max_steps + 1)]
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env_state = factory.reset()
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r = 0
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for agent_i_action in random_actions:
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env_state, step_r, done_bool, info_obj = factory.step(agent_i_action)
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r += step_r
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if render:
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factory.render()
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if done_bool:
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break
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print(f'Factory run {epoch} done, reward is:\n {r}')
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pass
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