arXiv subjects

Thomas Pike

Publications and source records attributed to Thomas Pike.

3 recordsLinked to original sources

arXiv2022

Social Networks as a Collective Intelligence: An Examination of the Python Ecosystem

The Python ecosystem represents a global, data rich, technology-enabled network. By analyzing Python's dependency network, its top 14 most imported libraries and cPython (or core Python) libraries, this research finds clear evidence the Python network can be considered a problem solving network. Analysis of the contributor network of the top 14 libraries and cPython reveals emergent specialization, where experts of specific libraries are isolated and focused while other experts link these critical libraries together, optimizing both local and global information exchange efficiency. As these networks are expanded, the local efficiency drops while the density increases, representing a possible transition point between exploitation (optimizing working solutions) and exploration (finding new solutions). These results provide insight into the optimal functioning of technology-enabled social networks and may have larger implications for the effective functioning of modern organizations.

cs.SI↗

arXiv2021

Growing the Simulation Ecosystem: Introducing Mesa Data to Provide Transparent, Accessible and Extensible Data Pipelines for Simulation Development

The Agent Based Model community has a rich and diverse ecosystem of libraries, platforms, and applications to help modelers develop rigorous simulations. Despite this robust and diverse ecosystem, the complexity of life from microbial communities to the global ecosystem still presents substantial challenges in making reusable code that can optimize the ability of the knowledge-sharing and reproducibility. This research seeks to provide new tools to mitigate some of these challenges by offering a vision of a more holistic ecosystem that takes researchers and practitioners from the data collection through validation, with transparent, accessible, and extensible subcomponents. This proposed approach is demonstrated through two data pipelines (crop yield and synthetic population) that take users from data download through the cleaning and processing until users of have data that can be integrated into an ABM. These pipelines are built to be transparent: by walking users step by step through the process, accessible: by being skill scalable so users can leverage them without code or with code, and extensible by being freely available on the coding sharing repository GitHub to facilitate community development. Reusing code that simulates complex phenomena is a significant challenge but one that must be consistently addressed to help the community move forward. This research seeks to aid that progress by offering potential new tools extended from the already robust ecosystem to help the community collaborate more effectively internally and across disciplines.

cs.CY↗

arXiv2019

Multi-Level Mesa

Multi-level Mesa is an extension to support the Python based Agents Based Model (ABM) library Mesa. Multi-level Mesa provides ABM infrastructure to allow for the inclusion of complex networks, which have modules (groups) and hierarchies (layers) of agents. This approach allows for users to define and simulate multi-layered adaptions of complex networks. This study reviews other multi-level libraries currently in the field, describes the main functions and classes of the Multi-level Mesa, and describes its implementation and impact in numerous varieties using the seminal ABM - Sugarscape. Multi-level Mesa and Sugarscape examples are available on GitHub at https://github.com/tpike3/multilevel_mesa and https://github.com/tpike3/SugarScape.

cs.MA↗