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Weird message, not sure what is this about #49

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nosyndicate opened this issue Oct 20, 2017 · 3 comments
Open

Weird message, not sure what is this about #49

nosyndicate opened this issue Oct 20, 2017 · 3 comments

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@nosyndicate
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Hi, I am curious if anyone run into this before.
I am using python version of the code, and sometime I saw message like this

base_left 11: [19141371, 0] lost turn? at [19141371, 0] sense=5296895 internal=5296896
base_left 11: [19141371, 0] lost turn_neck? at [19141371, 0] sense=19141372 internal=19141373
base_left 11: [19141374, 0] lost turn? at [19141374, 0] sense=5296898 internal=5296897
base_left 11: [19141374, 0] lost dash? at [19141374, 0] sense=13618895 internal=13618896
base_left 11: [19141375, 0] lost turn? at [19141375, 0] sense=5296898 internal=5296899
base_left 11: [19141375, 0] lost dash? at [19141375, 0] sense=13618896 internal=13618895
base_left 11: [19141378, 0] lost turn? at [19141378, 0] sense=5296901 internal=5296900
base_left 11: [19141378, 0] lost dash? at [19141378, 0] sense=13618896 internal=13618897
base_left 11: [19141379, 0] lost turn? at [19141379, 0] sense=5296901 internal=5296902
base_left 11: [19141379, 0] lost dash? at [19141379, 0] sense=13618897 internal=13618896
base_left 11: [19141381, 0] missed last action?(2) last decision=[19141379, 0]
base_left 11: [19141380, 0] lost turn? at [19141379, 0] sense=5296902 internal=5296901
base_left 11: [19141380, 0] lost turn_neck? at [19141379, 0] sense=19141381 internal=19141380
base_left 11: parser used several steps -- Missed an action?  sensory counts= 7  start_time= [19141379, 0]  end_time= [19141381, 0]
@DurgeshSamant
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Can you elaborate on how to reproduce this?
Which python version are you running?
What is the agent code that you are running?

@nosyndicate
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Sorry for getting back late, I am using the openai gym version of HFO https://github.com/openai/gym-soccer. My python version is 3.5.3 and I am applying some of my research code on this. However, reproducing this is not very easy, as the error usually showed up very late in the training process where the agent start to behave much better than random policy.

I am sorry that I could not give more details as I am also very busy on working on other stuff. I will try to dig more information out once I have time.

@mhauskn
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mhauskn commented Oct 31, 2017 via email

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3 participants