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@@ -18,6 +18,7 @@ For instance, you can think of a warehouse where **multiple robots need to navig
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<figure>
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<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit10/warehouse.jpg" alt="Warehouse"/>
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<figcaption> <a href="[https://www.freepik.com/free-vector/robots-warehouse-interior-automated-machines_32117680.htm#query=warehouse robot&position=17&from_view=keyword](https://www.freepik.com/free-vector/robots-warehouse-interior-automated-machines_32117680.htm#query=warehouse%20robot&position=17&from_view=keyword)">Image by upklyak</a> on Freepik </figcaption>
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</figure>
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Or a road with **several autonomous vehicles**.
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@@ -48,10 +49,7 @@ For example, in a game of tennis, **each agent wants to beat the other agent**.
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<figure>
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<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit10/soccertwos.gif" alt="SoccerTwos"/>
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<figcaption>This environment was made by the <a href="https://github.com/Unity-Technologies/ml-agents">Unity MLAgents Team</a></figcaption>
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</figure>
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<figcaption>This environment was made by the <a href="https://github.com/Unity-Technologies/ml-agents">Unity MLAgents Team</a></figcaption>
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So now we can ask how we design these multi-agent systems. Said differently, **how can we train agents in a multi-agents setting** ?
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