Fractalrabbit

<p align="center"> <a href="URL"> <img src="https://github.com/NationalSecurityAgency/fractalrabbit/blob/master/resources/Rabbit-CreativeCommonsImage..jpg" alt="" width=370 height=247> </a> <h3 align="center">FRACTALRABBIT</h3> <p> In modelling a sequence of adaptive choices by an intelligent agent (e.g. places visited, web sites browsed), memory-less random walks are unsuitable, because of the formation of agent habits and preferences. </p> <p> Often these choices are only partially observed, and report times are sporadic and bursty, in contrast to regular or exponentially spaced times in classical models. </p> <p> The FRACTALRABBIT stochastic mobility simulator creates realistic synthetic sporadic waypoint data sets. It consist of three tiers, each based on new stochastic models: </p> <p align="center"> (1) An Agoraphobic Point Process generates a set V of space points, whose limit is a random fractal, representing sites that could be visited. </p> <p align="center"> (2) A Retro-preferential Process generates a trajectory X through V , with strategic homing and self-reinforcing site fidelity as observed in human/animal behavior. </p> <p align="center"> (3) A Sporadic Reporting Process models time points T at which the trajectory X is observed, with bursts of reports and heavy tailed inter-event times.</p> </p> </p> <p> FRACTALRABBIT can be used to test algorithms applicable to sporadic waypoint data, such as (1) co-travel mining, (2) anomaly detection, and (3) extraction of maximal self-consistent subsets of corrupted data. <p> <p> Reference: R. W. R. Darling, "Retro-preferential Stochastic Mobility Models on Random Fractals Under Sporadic Observations", <a href = "https://www.researchgate.net/publication/340741639_Retro-preferential_Stochastic_Mobility_Models_on_Random_Fractals_Under_Sporadic_Observations">DOI: 10.13140/RG.2.2.15267.40489</a>, 2018 <p> <br>

Table of contents

• Status
• Bugs and feature requests
• Documentation
• Contributing
• Community
• Versioning
• Creators
• Copyright and license

Status

Java version runs from the command line:

<p> java -jar fractalrabbit.jar parameters.csv outputfilename.csv</p> <p> An example of the parameters.csv file is provided in the resources folder. Change it to suit your modelling needs. It permits multiple travellers to follow the same trajectory asynchronously. </p>

Bugs and feature requests

• Have a bug or a feature request? Contact Github user bbux-atg

Documentation

• See <a href="https://github.com/NationalSecurityAgency/fractalrabbit/wiki">Wiki</a>.

Contributing

• New implementations of the three underlying models described in the technical report are welcome.

Creators

R. W. R. Darling <a href=https://sites.google.com/view/probabilist-us/home>bio</a> Github: probabilist-us

Copyright and license

Apache License 2.0