Comments (6)
LucasAlegre
commented on May 30, 2024
Hi,
Hey,
When I run a3c_4x4grid.py, I get the error "AttributeError: 'TrafficLightDomain' object has no attribute 'getAllProgramLogics'".
Can you check whether you have sumo and sumo-tools updated and in the latest version (1.10)?
Can you please tell me how to make it work? When this error is fixed, I would like to run a map brought from OpenStreetMap. Will it work if I just rewrite the netfile?
Yes, the only restriction is that the traffic signals in your .net must be of the form:
green_phase (e.g. GGrr)
yellow_phase, (e.g. yyrr)
...,
green_phase,
yellow_phase
That is, it currently does not support all-red phases or phase configurations without yellow_phases.
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ryryryy
commented on May 30, 2024
The SUMO I installed wasn't the latest version, so I installed that!! Thanks !
The format of the traffic light is as follows But when I run it, I get this error.
traffic signals form
↓
`<tlLogic id="cluster_1069973586_1069974226" type="static" programID="0" offset="0">
<phase duration="40" state="GGGrrrGGG"/>
<phase duration="5" state="yyyrrryyy"/>
<phase duration="40" state="rrrGGGGrr"/>
<phase duration="5" state="rrryyyyrr"/>
</tlLogic>
<tlLogic id="cluster_1437173920_345567619" type="static" programID="0" offset="0">
<phase duration="33" state="GGGGGGrrrrr"/>
<phase duration="6" state="yyyyyyrrrrr"/>
<phase duration="6" state="rrrrGGGGrrr"/>
<phase duration="6" state="rrrryyyyrrr"/>
<phase duration="33" state="GrrrrrrrGGG"/>
<phase duration="6" state="yrrrrrrryyy"/>
</tlLogic>
<tlLogic id="cluster_2925460530_2925460531" type="static" programID="0" offset="0">
<phase duration="33" state="GGrrrrrGGGG"/>
<phase duration="6" state="yyrrrrryyyy"/>
<phase duration="6" state="GGGGrrrrrrr"/>
<phase duration="6" state="yyyyrrrrrrr"/>
<phase duration="33" state="rrrrGGGGrrr"/>
<phase duration="6" state="rrrryyyyrrr"/>
</tlLogic>
<tlLogic id="cluster_2925460919_2925460921_7005430268_7005430269" type="static" programID="0" offset="0">
<phase duration="33" state="GGGrrrrrGGGrrrrr"/>
<phase duration="6" state="yyyrrrrryyyrrrrr"/>
<phase duration="6" state="rrrGrrrrrrrGGrrr"/>
<phase duration="6" state="rrryrrrrrrryyrrr"/>
<phase duration="33" state="rrrrGGGGrrrrrGGG"/>
<phase duration="6" state="rrrryyyyrrrrryyy"/>
</tlLogic>
<tlLogic id="cluster_2926983387_2926983388_2926984764" type="static" programID="0" offset="0">
<phase duration="26" state="GGGGrrrrrrrr"/>
<phase duration="4" state="yyyyrrrrrrrr"/>
<phase duration="26" state="rrrrGGGGGrrr"/>
<phase duration="4" state="rrrryyyyyrrr"/>
<phase duration="26" state="GrrrrrrrGGGG"/>
<phase duration="4" state="yrrrrrrryyyy"/>
</tlLogic>
<tlLogic id="cluster_3191640061_384349108_384349109" type="static" programID="0" offset="0">
<phase duration="39" state="GGG"/>
<phase duration="6" state="yyy"/>
<phase duration="39" state="GGr"/>
<phase duration="6" state="yyr"/>
</tlLogic>
<tlLogic id="cluster_343364695_345567614" type="static" programID="0" offset="0">
<phase duration="33" state="GGGrrrrrrGGGrrrrrr"/>
<phase duration="6" state="yyyrrrrrryyyrrrrrr"/>
<phase duration="6" state="rrrGGrrrrrrrGGrrrr"/>
<phase duration="6" state="rrryyrrrrrrryyrrrr"/>
<phase duration="33" state="rrrrrGGGGrrrrrGGGG"/>
<phase duration="6" state="rrrrryyyyrrrrryyyy"/>
</tlLogic>
<tlLogic id="cluster_345565514_345567635" type="static" programID="0" offset="0">
<phase duration="33" state="GGGGGGrrrrr"/>
<phase duration="6" state="yyyyyyrrrrr"/>
<phase duration="6" state="rrrrGGGGrrr"/>
<phase duration="6" state="rrrryyyyrrr"/>
<phase duration="33" state="GrrrrrrrGGG"/>
<phase duration="6" state="yrrrrrrryyy"/>
</tlLogic>`error
↓
ValueError: ('Observation ({}) outside given space ({})!', array([1., 0., 0., 0., 0., 0., 0., 0.]), Box(0.0, 1.0, (20,), float32))
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LucasAlegre
commented on May 30, 2024
Hi, in your case you have traffic lights with different phases configurations/actions. Therefore, you need to use different rllib policies for each one of them.
You can do something like:
env = PettingZooEnv(sumo_rl.env(net_file='nets/4x4-Lucas/4x4.net.xml',
route_file='nets/4x4-Lucas/4x4c1c2c1c2.rou.xml',
out_csv_name='outputs/4x4grid/a3c',
use_gui=False,
num_seconds=80000,
max_depart_delay=0))
register_env("4x4grid", lambda _: PettingZooEnv(sumo_rl.env(net_file='nets/4x4-Lucas/4x4.net.xml',
route_file='nets/4x4-Lucas/4x4c1c2c1c2.rou.xml',
out_csv_name='outputs/4x4grid/a3c',
use_gui=False,
num_seconds=80000,
max_depart_delay=0)))
trainer = A3CTrainer(env="4x4grid", config={
"multiagent": {
"policies": {
id: (A3CTFPolicy, env.observation_spaces[id], env.action_spaces[id], {}) for id in env.agents
},
"policy_mapping_fn": (lambda id: id) # Traffic lights are always controlled by this policy
},
"lr": 0.001,
"no_done_at_end": True
})
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ryryryy
commented on May 30, 2024
I tried your advice and got the following error.
How can I fix this?
env = PettingZooEnv(sumo_rl.env(net_file='nets/OpenStreetMap/osm.net.xml',
route_file='nets/OpenStreetMap/osm.rou.xml',
out_csv_name='outputs/OpenStreetMap/osm',
use_gui=False,
num_seconds=80000,
max_depart_delay=0))
register_env("4x4grid", lambda _: PettingZooEnv(sumo_rl.env(net_file='nets/OpenStreetMap/osm.net.xml',
route_file='nets/OpenStreetMap/osm.rou.xml',
out_csv_name='outputs/OpenStreetMap/osm',
use_gui=False,
num_seconds=80000,
max_depart_delay=0)))
trainer = A3CTrainer(env="4x4grid", config={
"multiagent": {
"policies": {
id: (A3CTFPolicy, env.observation_spaces[id], env.action_spaces[id], {}) for id in env.agents
},
"policy_mapping_fn": (lambda id: id) # Traffic lights are always controlled by this policy
},
"lr": 0.001,
"no_done_at_end": True
})
while True:
print(trainer.train()) # distributed training step`
Error
↓
Observation spaces for all agents must be identical. Perhaps " \AssertionError: Observation spaces for all agents must be identical. Perhaps SuperSuit's pad_observations wrapper can help (useage: supersuit.aec_wrappers.pad_observations(env)
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LucasAlegre
commented on May 30, 2024
Closing as these are outdated.
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JenniferHahn
commented on May 30, 2024
I wanted to open this thread again since I am facing similar issues - I am trying to run multi-agent RL with a parallel petting zoo env which I am wrapping using superset (which creates the largest obs space for all) but I would actually like to have different policies for every agent since the action and observation space is initially different:
register_env(env_name, lambda config: ParallelPettingZooEnv(env_creator(config)))
env = PettingZooEnv(env_creator({}))
...
within the config I would like to set
.multiagent(
policies={id: (PPOTF1Policy, env.observation_spaces[id], env.action_spaces[id], {}) for id in env.agents},
policy_mapping_fn= (lambda id: id)
)
Is there any way to achieve both - use the (wrapped) environment but implement different policies?
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