docs(joss-paper): that comma...

.github/workflows/draft-pdf.yml

@@ -0,0 +1,25 @@
+name: Build Paper PDF
+
+on: [ push ]
+
+jobs:
+  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/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/paper.pdf

paper/paper.bib

@@ -0,0 +1,12 @@
+@InProceedings{python-mesa-2020,
+    author = "Kazil, Jackie and Masad, David and Crooks, Andrew",
+    editor = "Thomson, Robert and Bisgin, Halil and Dancy, Christopher and Hyder, Ayaz and Hussain, Muhammad",
+    title = "Utilizing Python for Agent-Based Modeling: The Mesa Framework",
+    booktitle = "Social, Cultural, and Behavioral Modeling",
+    year = "2020",
+    publisher = "Springer International Publishing",
+    address = "Cham",
+    pages = "308--317",
+    abstract = "Mesa is an agent-based modeling framework written in Python. Originally started in 2013, it was created to be the go-to tool in for researchers wishing to build agent-based models with Python. Within this paper we present Mesa's design goals, along with its underlying architecture. This includes its core components: 1) the model (Model, Agent, Schedule, and Space), 2) analysis (Data Collector and Batch Runner) and the visualization (Visualization Server and Visualization Browser Page). We then discuss how agent-based models can be created in Mesa. This is followed by a discussion of applications and extensions by other researchers to demonstrate how Mesa design is decoupled and extensible and thus creating the opportunity for a larger decentralized ecosystem of packages that people can share and reuse for their own needs. Finally, the paper concludes with a summary and discussion of future development areas for Mesa.",
+    isbn = "978-3-030-61255-9"
+}

paper/paper.md

@@ -0,0 +1,77 @@
+---
+title: 'Kami is Agent-Based Modeling in Modern C++'
+tags:
+  - C++
+  - agent-based model
+  - individual-based model
+  - social science
+  - simulation
+  - complex systems theory
+  - artificial life
+authors:
+  - name: "James P. Howard II"
+    orcid: 0000-0003-4530-1547
+    affiliation: 1
+affiliations:
+  - name: Johns Hopkins Applied Physics Laboratory, USA
+    index: 1
+date: 23 January 2023
+bibliography: paper.bib
+---
+
+# Summary
+
+Agent-based models (ABMs) are a type of computational model used
+to simulate the behavior of autonomous agents within a system. These
+agents can be individuals, groups, organizations, or other entities
+that interact with one another and with their environment. One of
+the key features of ABMs is that they focus on the micro-level
+interactions between individual agents, rather than aggregating
+data to study macro-level phenomena. This allows for the examination
+of complex behaviors that emerge from the interactions between
+agents, such as the spread of a disease or the formation of social
+networks. ABMs are often used in fields such as economics, sociology,
+and biology to study the behavior of individuals and groups. They
+can also be used to simulate the effects of different policies or
+interventions on a system.
+
+# Statement of need
+
+There are many different agent-based modeling (ABM) platforms
+available for use in Java, Javascript, Python, and other programming
+languages. Many others are implemented in domain-specific languages
+that allow for the rapid development of complex models. However,
+running interpreted, these models are slower than that offered by
+compiled systems. There are several application-specific ABMs
+available for specific problems, including public health, ecology,
+economics, and other fields. Kami aims to fill a niche
+for implementing a field-neutral, extensible ABM platform in modern
+C++, using C++17 as a baseline for requirements.
+
+Kami provides support for multiple agent classes, population
+management, scheduling management, and environmental management
+classes. The package provides examples of three relatively simple
+ABMs: a bank reserves model, a one-dimensional Boltzmann wealth
+model, and a two-dimensional Boltzmann wealth model. The package
+provides examples of both a minimal ABM implemented with Kami, as
+well as a starter ABM, either of which is suitable for beginning a
+new investigation using Kami. Finally, the library provides extensive
+unit-testing for all of the internal classes.
+
+Kami's interface is heavily influenced by Mesa's interface
+[@python-mesa-2020]. However, being written in C++, Kami runs
+substantially faster. This allows for faster runs and more runs
+within a fixed amount of time. The advantage here is that an ABM
+built on the Kami platform is better suited for statistical and
+Monte Carlo approaches to modeling.
+
+An interest design note is that Kami does not use any form of
+parallel processing due to the complexities of managing random
+number generators and providing reproducibility in results for a
+given random number seed. However, it is suitable to run as many
+instances of Kami-based models simultaneously as hardware threading
+can permit. A final design note is that Kami is opinionated in
+that it prefers inheritance to composition in model design and
+further, templates are not used for metaprogramming.
+
+# References