Fix paper issues seen in review (#47)

Author: MathisFederico

.github/workflows/pydoc-github-pages.yml

@@ -19,26 +19,21 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v3
-      - uses: actions/setup-python@v4
-        with:
-          python-version: '3.11'
-
-    - uses: actions/checkout@v2
-    - name: Install uv
-      uses: astral-sh/setup-uv@v5
-    - name: Set up venv with Python ${{ matrix.python-version }}
-      run: |
-        uv venv --python ${{ matrix.python-version }}
-    - name: Install dependencies
-      run: |
-        uv sync --extra docs --extra gym --extra gui --extra planning --extra htmlvis
-    - name: Make documentation
-    - run: |
-        uv run pdoc -d google -t docs/template --logo https://irll.net/irll-logo.png --logo-link https://irll.github.io/HierarchyCraft/hcraft.html -o docs/build --math --no-search hcraft
-    - name: Upload static documentation artifact
-      - uses: actions/upload-pages-artifact@v1
-        with:
-          path: docs/build
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+      - name: Set up venv with Python ${{ matrix.python-version }}
+        run: |
+          uv venv --python ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: |
+          uv sync --extra docs --extra gym --extra gui --extra planning --extra htmlvis
+      - name: Make documentation
+      - run: |
+          uv run pdoc -d google -t docs/template --logo https://irll.net/irll-logo.png --logo-link https://irll.github.io/HierarchyCraft/hcraft.html -o docs/build --math --no-search hcraft
+      - name: Upload static documentation artifact
+        - uses: actions/upload-pages-artifact@v1
+          with:
+            path: docs/build
 
   # Deploy the artifact to GitHub pages.
   # This is a separate job so that only actions/deploy-pages has the necessary permissions.

README.md

@@ -22,7 +22,7 @@ The action space of HierarchyCraft environments consists of sub-tasks, referred
 This concept is visually represented by the *Requirements graph* depicting the hierarchical relationships within each HierarchyCraft environment.
 The *Requirements graph* is directly constructed from the list of *Transformations* composing the environement.
 
-![](docs/images/TransformationToRequirementsLarge.png)
+![](docs/images/TransformationToRequirements.png)
 
 More details about requirements graph can be found in the documentation at [`hcraft.requirements`](https://irll.github.io/HierarchyCraft/hcraft/requirements.html) and example of requirements graph for some HierarchyCraft environements can be found in [`hcraft.examples`](https://irll.github.io/HierarchyCraft/hcraft/examples.html).
 

paper.bib

@@ -34,11 +34,14 @@ @article{sutton1999between
   publisher={Elsevier}
 }
 
-@software{minigrid,
-  author = {Chevalier-Boisvert, Maxime and Willems, Lucas and Pal, Suman},
-  title = {Minimalistic Gridworld Environment for Gymnasium},
-  url = {https://github.com/Farama-Foundation/Minigrid},
-  year = {2018},
+
+@inproceedings{minigrid,
+  author       = {Maxime Chevalier{-}Boisvert and Bolun Dai and Mark Towers and Rodrigo Perez{-}Vicente and Lucas Willems and Salem Lahlou and Suman Pal and Pablo Samuel Castro and Jordan Terry},
+  title        = {Minigrid {\&} Miniworld: Modular {\&} Customizable Reinforcement Learning Environments for Goal-Oriented Tasks},
+  booktitle    = {Advances in Neural Information Processing Systems 36, New Orleans, LA, USA},
+  month        = {December},
+  year         = {2023},
+  url          = {https://github.com/Farama-Foundation/Minigrid},
 }
 
 @article{machado2018revisiting,
@@ -232,3 +235,51 @@ @InProceedings{2021NetHack
   url = 	 {https://proceedings.mlr.press/v176/hambro22a.html},
   abstract = 	 {In this report, we summarize the takeaways from the first NeurIPS 2021 NetHack Challenge. Participants were tasked with developing a program or agent that can win (i.e., ’ascend’ in) the popular dungeon-crawler game of NetHack by interacting with the NetHack Learning Environment (NLE), a scalable, procedurally generated, and challenging Gym environment for reinforcement learning (RL). The challenge showcased community-driven progress in AI with many diverse approaches significantly beating the previously best results on NetHack. Furthermore, it served as a direct comparison between neural (e.g., deep RL) and symbolic AI, as well as hybrid systems, demonstrating that on NetHack symbolic bots currently outperform deep RL by a large margin. Lastly, no agent got close to winning the game, illustrating NetHack’s suitability as a long-term benchmark for AI research.}
 }
+
+@article{botvinick2014model,
+  title={Model-based hierarchical reinforcement learning and human action control},
+  author={Botvinick, Matthew and Weinstein, Aaron},
+  journal={Philosophical Transactions of the Royal Society B: Biological Sciences},
+  volume={369},
+  number={1655},
+  pages={20130480},
+  year={2014},
+  publisher={The Royal Society}
+}
+
+@inproceedings{bacon2017option,
+  title={The option-critic architecture},
+  author={Bacon, Pierre-Luc and Harb, Mohamad and Precup, Doina},
+  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
+  volume={31},
+  number={1},
+  year={2017}
+}
+
+@inproceedings{heess2016learning,
+  title={Learning continuous control policies by stochastic value gradients},
+  author={Heess, Nicolas and Wayne, Greg and Silver, David and Lillicrap, Timothy and Erez, Tom and Tassa, Yuval},
+  booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
+  volume={29},
+  pages={2944--2952},
+  year={2016}
+}
+@inproceedings{nachum2018data,
+  title={Data-efficient hierarchical reinforcement learning},
+  author={Nachum, Ofir and Gu, Shixiang and Lee, Honglak and Levine, Sergey},
+  booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
+  volume={31},
+  pages={3303--3313},
+  year={2018}
+}
+
+@article{Chollet2019OnTM,
+  title={On the Measure of Intelligence},
+  author={François Chollet},
+  journal={ArXiv},
+  year={2019},
+  volume={abs/1911.01547},
+  url={https://api.semanticscholar.org/CorpusID:207870692}
+}
+
+