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@@ -112,7 +112,7 @@ Registered configurations:
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- `MiniGrid-Empty-16x16-v0`
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- `MiniGrid-Empty-16x16-v0`
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<p align="center">
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<p align="center">
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-<img src="/figures/empty-env.png">
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+<img src="/figures/empty-env.png" width=250>
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</p>
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</p>
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This environment is an empty room, and the goal of the agent is to reach the
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This environment is an empty room, and the goal of the agent is to reach the
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@@ -153,7 +153,7 @@ square the agent must get to. This environment is extremely difficult to
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solve using classical RL. However, by gradually increasing the number of
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solve using classical RL. However, by gradually increasing the number of
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rooms and building a curriculum, the environment can be solved.
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rooms and building a curriculum, the environment can be solved.
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-### Go to door environment
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+### Go-to-door environment
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Registered configurations:
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Registered configurations:
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- `MiniGrid-GoToDoor-5x5-v0`
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- `MiniGrid-GoToDoor-5x5-v0`
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@@ -161,7 +161,7 @@ Registered configurations:
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- `MiniGrid-GoToDoor-8x8-v0`
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- `MiniGrid-GoToDoor-8x8-v0`
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<p align="center">
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<p align="center">
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-<img src="/figures/gotodoor-6x6.png">
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+<img src="/figures/gotodoor-6x6.png" width=400>
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</p>
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</p>
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This environment is a room with four doors, one on each wall. The agent
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This environment is a room with four doors, one on each wall. The agent
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@@ -176,7 +176,7 @@ Registered configurations:
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- `MiniGrid-Fetch-8x8-N3-v0`
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- `MiniGrid-Fetch-8x8-N3-v0`
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<p align="center">
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<p align="center">
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-<img src="/figures/fetch-env.png" width=392 height=269>
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+<img src="/figures/fetch-env.png" width=450>
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</p>
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</p>
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This environment has multiple objects of assorted types and colors. The
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This environment has multiple objects of assorted types and colors. The
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Maxime Chevalier-Boisvert