<p>I thought about my input-layer. I had the 500 states one hot encoded. So 499 of every input node would be 0. And 0 is very bad in an neural network. I tried the same code with the "CardPole-v0" and it worked. </p>

<p>So think about your input guys </p>

CC BY-SA 4.0
2020-01-16T11:02:36.260Z
2020-01-16T11:02:36.260Z
Voß
<p>I'm trying to implement deep q learning in the OpenAI's gym "Taxi-v3" environment. But my agent only learns to do one action in every state. What am I doing wrong? Here is the <a href="https://github.com/OleVoss/DeepTaxi" rel="nofollow noreferrer">Github repository with the code</a>.</p>

<deep-learning><reinforcement-learning><open-ai><pytorch><gym>
Why is this deep Q agent constantly learning just one action?
Voß
# Why is this deep Q agent constantly learning just one action?

(Asked by: username_0 on 2020-01-16)

I'm trying to implement deep q learning in the OpenAI's gym "Taxi-v3" environment. But my agent only learns to do one action in every state. What am I doing wrong? Here is the [Github repository with the code](https://github.com/OleVoss/DeepTaxi).

**Tags:** deep-learning, reinforcement-learning, open-ai, pytorch, gym


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## 1 answers

### Answer by username_0 on 2020-01-16. Score: 1 | Accepted answer

I thought about my input-layer. I had the 500 states one hot encoded. So 499 of every input node would be 0. And 0 is very bad in an neural network. I tried the same code with the "CardPole-v0" and it worked.

So think about your input guys


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