Comments (1)
The observation space on this experiment was wrong.
I fixed it in my last commit, it should work now.
Thanks!
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Related Issues (20)
- name 'policy' is not defined HOT 1
- Environment sumo-rl doesn't exist. HOT 3
- plot.py ERROR HOT 3
- self.sumo.trafficlight.setRedYellowGreenState ERROR HOT 7
- TypeError: float() argument must be a string or a number, not 'dict' HOT 1
- working on 4x4 intersection HOT 1
- How do I run the trained model HOT 2
- The algorithm only supports (<class 'gym.spaces.discrete.Discrete'>,) as action spaces but Discrete(4) was provided HOT 4
- Gym -> Gymnasium HOT 4
- AssertionError HOT 3
- single-intersection:Numpy RuntimeWarning HOT 4
- _compute_dones wrong? HOT 1
- 'aec_to_parallel_wrapper' object has no attribute 'agents' HOT 1
- Clarification on TLS phases HOT 2
- default output files HOT 4
- Test already trained A3C policy on 4x4 grid HOT 3
- Error with learn() when running example sb3_4x4grid.py
- About sumo_cmd HOT 3
- info dicts not returning populated with metrics in multiagent api HOT 5
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