Putting together a draft paper for JOSS

.github/workflows/CI.yml

@@ -117,6 +117,26 @@ jobs:
         with:
           src: doc-coverage.json
           dst: stats/doc-coverage.json
+  paper:
+    runs-on: ubuntu-latest
+    name: Paper Draft
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Build draft PDF
+        uses: openjournals/openjournals-draft-action@master
+        with:
+          journal: joss
+          # This should be the path to the paper within your repo.
+          paper-path: paper.md
+      - name: Upload
+        uses: actions/upload-artifact@v1
+        with:
+          name: paper
+          # This is the output path where Pandoc will write the compiled
+          # PDF. Note, this should be the same directory as the input
+          # paper.md
+          path: paper.pdf
   deploy-dockerhub:
     name: Deploy to DockerHub
     runs-on: ubuntu-18.04

paper.bib

@@ -0,0 +1,269 @@
+@inproceedings{haas2017bringing,
+  title={Bringing the web up to speed with WebAssembly},
+  author={Haas, Andreas and Rossberg, Andreas and Schuff, Derek L and Titzer, Ben L and Holman, Michael and Gohman, Dan and Wagner, Luke and Zakai, Alon and Bastien, JF},
+  booktitle={Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation},
+  pages={185--200},
+  year={2017},
+  month={6},
+  url={http://dx.doi.org/10.1145/3062341.3062363},
+  doi={10.1145/3062341.3062363},
+  publisher={Association for Computing Machinery}
+}
+
+@inproceedings{jangda2019not,
+  title={Not so fast: Analyzing the performance of webassembly vs. native code},
+  author={Jangda, Abhinav and Powers, Bobby and Berger, Emery D and Guha, Arjun},
+  booktitle={2019 $\{$USENIX$\}$ Annual Technical Conference ($\{$USENIX$\}$$\{$ATC$\}$ 19)},
+  pages={107--120},
+  year={2019},
+  month={7},
+  isbn={9781939133038},
+  url={https://www.usenix.org/conference/atc19/presentation/jangda},
+  publisher={USENIX Association}
+}
+
+@article{kazi2000techniques,
+  title={Techniques for obtaining high performance in Java programs},
+  author={Kazi, Iffat H and Chen, Howard H and Stanley, Berdenia and Lilja, David J},
+  journal={ACM Computing Surveys (CSUR)},
+  volume={32},
+  number={3},
+  pages={213--240},
+  year={2000},
+  month={9},
+  url={https://doi.org/10.1145/367701.367714},
+  doi={10.1145/367701.367714},
+  publisher={ACM New York, NY, USA}
+}
+
+@article{widynski2020squares,
+  title={Squares: A Fast Counter-Based RNG},
+  author={Widynski, Bernard},
+  journal={arXiv preprint arXiv:2004.06278},
+  year={2020},
+  month={11},
+  url={https://arxiv.org/abs/2004.06278v3},
+  publisher={Cornell University}
+}
+
+@article{pennock2007learning,
+  title={LEARNING EVOLUTION AND THE NATURE OF SCIENCE USING EVOLUTIONARY COMPUTING AND ARTIFICIAL LIFE/APPRENDRE L’{\'E}VOLUTION ET LA NATURE DES SCIENCES AU MOYEN DU CALCUL {\'E}VOLUTIONNISTE ET DE LA VIE ARTIFICIELLE},
+  author={Pennock, Robert T},
+  journal={McGill Journal of Education/Revue des sciences de l'{\'e}ducation de McGill},
+  volume={42},
+  number={2},
+  year={2007},
+  month={10},
+  url={https://mje.mcgill.ca/article/view/2220},
+  publisher={McGill University}
+}
+
+@inproceedings{zakai2011emscripten,
+  title={Emscripten: an LLVM-to-JavaScript compiler},
+  author={Zakai, Alon},
+  booktitle={Proceedings of the ACM international conference companion on Object oriented programming systems languages and applications companion},
+  pages={301--312},
+  year={2011},
+  month={10},
+  doi={10.1145/2048147.2048224},
+  url={http://dx.doi.org/10.1145/2048147.2048224},
+  publisher={Association for Computing Machinery}
+}
+
+@article{richmond2010high,
+  title={High performance cellular level agent-based simulation with FLAME for the GPU},
+  author={Richmond, Paul and Walker, Dawn and Coakley, Simon and Romano, Daniela},
+  journal={Briefings in bioinformatics},
+  volume={11},
+  number={3},
+  pages={334--347},
+  year={2010},
+  month={2},
+  doi={10.1093/bib/bbp073},
+  url={https://doi.org/10.1093/bib/bbp073},
+  publisher={Oxford University Press}
+}
+
+@inproceedings{tisue2004netlogo,
+  title={Netlogo: A simple environment for modeling complexity},
+  author={Tisue, Seth and Wilensky, Uri},
+  booktitle={International conference on complex systems},
+  volume={21},
+  pages={16--21},
+  year={2004},
+  url={http://ccl.northwestern.edu/papers/netlogo-iccs2004.pdf},
+  organization={Boston, MA}
+}
+
+@Manual{chang2020shiny,
+  title = {shiny: Web Application Framework for R},
+  author = {Winston Chang and Joe Cheng and JJ Allaire and Yihui Xie and Jonathan McPherson},
+  year = {2020},
+  note = {R package version 1.5.0},
+  url = {https://CRAN.R-project.org/package=shiny}
+}
+
+@Manual{developers2021pyodide,
+  title= {shiny: Web Application Framework for R},
+  author = {Michael Droettboom and Pyodide Developers},
+  year = {2021},
+  note = {Python package version 0.0.17},
+  url = {https://pyodide.org/}
+}
+
+@article{helikar2012cell,
+  title={The cell collective: toward an open and collaborative approach to systems biology},
+  author={Helikar, Tom{\'a}{\v{s}} and Kowal, Bryan and McClenathan, Sean and Bruckner, Mitchell and Rowley, Thaine and Madrahimov, Alex and Wicks, Ben and Shrestha, Manish and Limbu, Kahani and Rogers, Jim A},
+  journal={BMC systems biology},
+  volume={6},
+  number={1},
+  pages={1--14},
+  year={2012},
+  month={8},
+  doi={10.1186/1752-0509-6-96},
+  url={https://doi.org/10.1186/1752-0509-6-96},
+  publisher={Springer}
+}
+
+@book{vostinar2017suicide,
+  title={Suicide, signals, and symbionts: Evolving cooperation in agent-based systems},
+  author={Vostinar, Anya E},
+  year={2017},
+  url={https://proxy.lib.umich.edu/login?url=https://www.proquest.com/dissertations-theses/suicide-signals-symbionts-evolving-cooperation/docview/1929231148/se-2?accountid=14667},
+  isbn={978-0-355-07992-0},
+  publisher={Michigan State University}
+}
+
+@article{gillespie2018changing,
+  title={Changing Environments Drive the Separation of Genes and Increased Evolvability in NK-Inspired Landscapes},
+  author={Gillespie, Lauren and Dolson, Emily and Lalejini, Alexander and Ofria, Charles},
+  year={2018},
+  journal={Late breaking abstract at The 2018 Conference on Artificial Life}
+}
+
+@inproceedings{Lalejini2018-GECCO,
+  abstract = {We present SignalGP, a new genetic programming (GP) technique designed to incorporate the event-driven programming paradigm into computational evolution's toolbox. Event-driven programming is a software design philosophy that simplifies the development of reactive programs by automatically triggering program modules (event-handlers) in response to external events, such as signals from the environment or messages from other programs. SignalGP incorporates these concepts by extending existing tag-based referencing techniques into an event-driven context. Both events and functions are labeled with evolvable tags; when an event occurs, the function with the closest matching tag is triggered. In this work, we apply SignalGP in the context of linear GP. We demonstrate the value of the event-driven paradigm using two distinct test problems (an environment coordination problem and a distributed leader election problem) by comparing SignalGP to variants that are otherwise identical, but must actively use sensors to process events or messages. In each of these problems, rapid interaction with the environment or other agents is critical for maximizing fitness. We also discuss ways in which SignalGP can be generalized beyond our linear GP implementation.},
+  address = {New York, New York, USA},
+  archivePrefix = {arXiv},
+  arxivId = {1804.05445},
+  author = {Lalejini, Alexander and Ofria, Charles},
+  booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '18},
+  doi = {10.1145/3205455.3205523},
+  eprint = {1804.05445},
+  isbn = {9781450356183},
+  keywords = {event-driven computation,event-driven programming,genetic programming,linear genetic programming,signalgp,tags},
+  pages = {1135--1142},
+  publisher = {ACM Press},
+  title = {{Evolving event-driven programs with SignalGP}},
+  url = {http://arxiv.org/abs/1804.05445{\%}0Ahttp://dx.doi.org/10.1145/3205455.3205523 http://dl.acm.org/citation.cfm?doid=3205455.3205523},
+  year = {2018}
+}
+
+@article{moreno2019toward,
+    author = {Moreno, Matthew Andres and Ofria, Charles},
+    title = "{Toward Open-Ended Fraternal Transitions in Individuality}",
+    journal = {Artificial Life},
+    volume = {25},
+    number = {2},
+    pages = {117-133},
+    year = {2019},
+    month = {05},
+    abstract = "{The emergence of new replicating entities from the union of simpler entities characterizes some of the most profound events in natural evolutionary history. Such transitions in individuality are essential to the evolution of the most complex forms of life. Thus, understanding these transitions is critical to building artificial systems capable of open-ended evolution. Alas, these transitions are challenging to induce or detect, even with computational organisms. Here, we introduce the DISHTINY (Distributed Hierarchical Transitions in Individuality) platform, which provides simple cell-like organisms with the ability and incentive to unite into new individuals in a manner that can continue to scale to subsequent transitions. The system is designed to encourage these transitions so that they can be studied: Organisms that coordinate spatiotemporally can maximize the rate of resource harvest, which is closely linked to their reproductive ability. We demonstrate the hierarchical emergence of multiple levels of individuality among simple cell-like organisms that evolve parameters for manually designed strategies. During evolution, we observe reproductive division of labor and close cooperation among cells, including resource-sharing, aggregation of resource endowments for propagules, and emergence of an apoptosis response to somatic mutation. Many replicate populations evolved to direct their resources toward low-level groups (behaving like multicellular individuals), and many others evolved to direct their resources toward high-level groups (acting as larger-scale multicellular individuals).}",
+    issn = {1064-5462},
+    doi = {10.1162/artl_a_00284},
+    url = {https://doi.org/10.1162/artl\_a\_00284},
+    eprint = {https://direct.mit.edu/artl/article-pdf/25/2/117/1896700/artl\_a\_00284.pdf},
+}
+
+@article{collier2013parallel,
+author = {Nicholson Collier and Michael North},
+title ={Parallel agent-based simulation with Repast for High Performance Computing},
+journal = {SIMULATION},
+volume = {89},
+number = {10},
+pages = {1215-1235},
+year = {2013},
+month={11},
+doi = {10.1177/0037549712462620},
+
+URL = { 
+        https://doi.org/10.1177/0037549712462620
+
+},
+eprint = { 
+        https://doi.org/10.1177/0037549712462620
+
+}
+,
+    abstract = { In the last decade, agent-based modeling and simulation (ABMS) has been applied to a variety of domains, demonstrating the potential of this technique to advance science, engineering, and policy analysis. However, realizing the full potential of ABMS to find breakthrough research results requires far greater computing capability than is available through current ABMS tools. The Repast for High Performance Computing (Repast HPC) project addresses this need by developing a useful and useable next-generation ABMS system explicitly focusing on larger-scale distributed computing platforms. Repast HPC is intended to smooth the path from small-scale simulations to large-scale distributed simulations through the use of a Logo-like system. This article’s contribution is its detailed presentation of the implementation of Repast HPC as a useful and usable framework, a complete ABMS platform developed explicitly for larger-scale distributed computing systems that leverages modern C++ techniques and the ReLogo language. }
+}
+
+@article{north2013complex,
+  title={Complex adaptive systems modeling with Repast Simphony},
+  author={North, Michael J and Collier, Nicholson T and Ozik, Jonathan and Tatara, Eric R and Macal, Charles M and Bragen, Mark and Sydelko, Pam},
+  journal={Complex adaptive systems modeling},
+  volume={1},
+  number={1},
+  pages={1--26},
+  year={2013},
+  month={3},
+  doi={10.1186/2194-3206-1-3},
+  url={https://doi.org/10.1186/2194-3206-1-3},
+  publisher={Springer}
+}
+
+@inproceedings{dolson2018evological,
+author = {Dolson, Emily and Ofria, Charles},
+title = {Ecological Theory Provides Insights about Evolutionary Computation},
+year = {2018},
+isbn = {9781450357647},
+publisher = {Association for Computing Machinery},
+address = {New York, NY, USA},
+url = {https://doi.org/10.1145/3205651.3205780},
+doi = {10.1145/3205651.3205780},
+abstract = {Promoting diversity in an evolving population is important for Evolutionary Computation (EC) because it reduces premature convergence on suboptimal fitness peaks while still encouraging both exploration and exploitation [3]. However, some types of diversity facilitate finding global optima better than other types. For example, a high mutation rate may maintain high population-level diversity, but all of those genotypes are clustered in a local region of a fitness landscape. Fitness sharing [3], on the other hand, promotes diversity via negative density dependence forcing solutions apart. Lexicase selection [5] goes one step further, dynamically selecting for diverse phenotypic traits, encouraging solutions to actively represent many portions of the landscape.},
+booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference Companion},
+pages = {105–106},
+numpages = {2},
+keywords = {ecological theory, diversity maintenance, eco-evolutionary dynamics, fitness sharing, phylogenetic analysis, ecology, lexicase selection, diversity, eco-EA},
+location = {Kyoto, Japan},
+series = {GECCO '18}
+}
+
+@software{moreno2020conduit,
+  author       = {Matthew Andres Moreno and
+                  rodsan0 and
+                  perryk12 and
+                  Codacy Badger},
+  title        = {mmore500/conduit: Initial release},
+  month        = oct,
+  year         = 2020,
+  publisher    = {Zenodo},
+  version      = {v0.1.0},
+  doi          = {10.5281/zenodo.4118608},
+  url          = {https://doi.org/10.5281/zenodo.4118608}
+}
+
+ @misc{world_academy_of_science_engineering_and_technology_2019, title={ Open Science Philosophy}, url={https://waset.org/files/Open-Science-Philosophy.pdf}, journal={World Academy of Science, Engineering and Technology}, year={2019}} 
+
+@article{10.1145/3185517,
+author = {Dudley, John J. and Kristensson, Per Ola},
+title = {A Review of User Interface Design for Interactive Machine Learning},
+year = {2018},
+issue_date = {July 2018},
+publisher = {Association for Computing Machinery},
+address = {New York, NY, USA},
+volume = {8},
+number = {2},
+issn = {2160-6455},
+url = {https://doi.org/10.1145/3185517},
+doi = {10.1145/3185517},
+abstract = {Interactive Machine Learning (IML) seeks to complement human perception and intelligence by tightly integrating these strengths with the computational power and speed of computers. The interactive process is designed to involve input from the user but does not require the background knowledge or experience that might be necessary to work with more traditional machine learning techniques. Under the IML process, non-experts can apply their domain knowledge and insight over otherwise unwieldy datasets to find patterns of interest or develop complex data-driven applications. This process is co-adaptive in nature and relies on careful management of the interaction between human and machine. User interface design is fundamental to the success of this approach, yet there is a lack of consolidated principles on how such an interface should be implemented. This article presents a detailed review and characterisation of Interactive Machine Learning from an interactive systems perspective. We propose and describe a structural and behavioural model of a generalised IML system and identify solution principles for building effective interfaces for IML. Where possible, these emergent solution principles are contextualised by reference to the broader human-computer interaction literature. Finally, we identify strands of user interface research key to unlocking more efficient and productive non-expert interactive machine learning applications.},
+journal = {ACM Trans. Interact. Intell. Syst.},
+month = jun,
+articleno = {8},
+numpages = {37},
+keywords = {interface design, Interactive machine learning}
+}
+
+@article{empirical_2020, title={devosoft/Empirical}, DOI={10.5281/zenodo.2575606}, publisher={Zenodo}, author={Charles Ofria and Matthew Andres Moreno and Emily Dolson and Alex Lalejini and rodsan0 and Jake Fenton and perryk12 and Steven Jorgensen and hoffmanriley and grenewode and et al.}, year={2020}, month={Oct}}