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Update snowball-target.mdx

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Thomas Simonini
2023-01-07 17:36:28 +01:00
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units/en/unit5/snowball-target.mdx
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@@ -19,14 +19,15 @@ In addition, to avoid "snowball spamming" (aka shooting a snowball every timeste
The reward function is simple. **The environment gives a +1 reward every time the agent's snowball hits a target** and because the agent's goal is to maximize the expected cumulative reward, **it will try to hit as many targets as possible**.
In terms of code it looks like this:
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit5/snowballtarget-reward-code.png" alt="Reward"/>
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit7/snowballtarget_reward.png" alt="Reward system"/>
We could have a more complex reward function (with a penalty to push the agent to go faster, etc.). But when you design an environment, you need to avoid the *reward engineering problem*, which is having a too complex reward function to force your agent to behave as you want it to do.
Why? Because by doing that, **you might miss interesting strategies that the agent will find with a simpler reward function**.
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit7/snowballtarget_reward.png" alt="Reward system"/>
In terms of code it looks like this:
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit5/snowballtarget-reward-code.png" alt="Reward"/>
## The observation space