{"id":19582892,"url":"https://github.com/nationalsecurityagency/fractalrabbit","last_synced_at":"2025-04-04T12:07:44.735Z","repository":{"id":42056601,"uuid":"128101452","full_name":"NationalSecurityAgency/fractalrabbit","owner":"NationalSecurityAgency","description":"Simulate realistic trajectory data seen through sporadic reporting","archived":false,"fork":false,"pushed_at":"2025-02-22T20:54:33.000Z","size":9310,"stargazers_count":154,"open_issues_count":0,"forks_count":52,"subscribers_count":17,"default_branch":"master","last_synced_at":"2025-03-28T11:08:25.266Z","etag":null,"topics":["algorithm-analysis","probabilistic-models","simulation-modeling"],"latest_commit_sha":null,"homepage":"","language":"Java","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/NationalSecurityAgency.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-04-04T18:07:04.000Z","updated_at":"2025-03-21T18:12:19.000Z","dependencies_parsed_at":"2024-04-23T21:19:08.554Z","dependency_job_id":"94807aa8-9228-4c17-be93-c7a8c681100d","html_url":"https://github.com/NationalSecurityAgency/fractalrabbit","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/NationalSecurityAgency%2Ffractalrabbit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/NationalSecurityAgency%2Ffractalrabbit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/NationalSecurityAgency%2Ffractalrabbit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/NationalSecurityAgency%2Ffractalrabbit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/NationalSecurityAgency","download_url":"https://codeload.github.com/NationalSecurityAgency/fractalrabbit/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247174418,"owners_count":20896078,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["algorithm-analysis","probabilistic-models","simulation-modeling"],"created_at":"2024-11-11T07:38:28.009Z","updated_at":"2025-04-04T12:07:44.714Z","avatar_url":"https://github.com/NationalSecurityAgency.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\r\n  \u003ca href=\"URL\"\u003e\r\n    \u003cimg src=\"https://github.com/NationalSecurityAgency/fractalrabbit/blob/master/resources/Rabbit-CreativeCommonsImage..jpg\" alt=\"\" width=370 height=247\u003e\r\n  \u003c/a\u003e\r\n\r\n  \u003ch3 align=\"center\"\u003eFRACTALRABBIT\u003c/h3\u003e\r\n\u003cp\u003e\r\nIn 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. \r\n \u003c/p\u003e\r\n\r\n\u003cp\u003e\r\n 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. \r\n\u003c/p\u003e\r\n\r\n\u003cp\u003e\r\nThe FRACTALRABBIT stochastic mobility simulator creates realistic synthetic sporadic waypoint data sets. It consist of three tiers, each based on new stochastic models: \u003c/p\u003e\r\n\r\n  \u003cp align=\"center\"\u003e\t\r\n\t (1) An Agoraphobic Point Process generates a set V of space points, whose limit is a random fractal, representing sites that could be visited. \u003c/p\u003e\r\n\r\n  \u003cp align=\"center\"\u003e\t(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. \u003c/p\u003e\r\n\r\n  \u003cp align=\"center\"\u003e\t (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.\u003c/p\u003e\r\n  \u003c/p\u003e\r\n\u003c/p\u003e\r\n\u003cp\u003e\r\n 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.\r\n\u003cp\u003e\r\n\u003cp\u003e\r\nReference: R. W. R. Darling, \"Retro-preferential Stochastic Mobility Models on Random Fractals Under Sporadic Observations\", \r\n\u003ca href = \"https://www.researchgate.net/publication/340741639_Retro-preferential_Stochastic_Mobility_Models_on_Random_Fractals_Under_Sporadic_Observations\"\u003eDOI: 10.13140/RG.2.2.15267.40489\u003c/a\u003e, 2018\r\n\u003cp\u003e\r\n\r\n\u003cbr\u003e\r\n\r\n## Table of contents\r\n\r\n- [Status](#status)\r\n- [Bugs and feature requests](#bugs-and-feature-requests)\r\n- [Documentation](#documentation)\r\n- [Contributing](#contributing)\r\n- [Community](#community)\r\n- [Versioning](#versioning)\r\n- [Creators](#creators)\r\n- [Copyright and license](#copyright-and-license)\r\n\r\n## Status\r\nJava version runs from the command line:\r\n\u003cp\u003e\r\n\tjava -jar fractalrabbit.jar parameters.csv outputfilename.csv\u003c/p\u003e\r\n\u003cp\u003e\t\r\nAn example of the parameters.csv file is provided in the resources folder.\r\nChange it to suit your modelling needs. \r\nIt permits multiple travellers to follow the same trajectory asynchronously.\r\n\u003c/p\u003e\t\r\n\r\n## Bugs and feature requests\r\n- Have a bug or a feature request? Contact Github user bbux-atg\r\n\r\n## Documentation\r\n- See \u003ca href=\"https://github.com/NationalSecurityAgency/fractalrabbit/wiki\"\u003eWiki\u003c/a\u003e. \r\n\r\n## Contributing\r\n- New implementations of the three underlying models described in the technical report are welcome.\r\n\r\n## Creators\r\n\r\n**R. W. R. Darling**\r\n\u003ca href=https://sites.google.com/view/probabilist-us/home\u003ebio\u003c/a\u003e\r\nGithub: probabilist-us\r\n\r\n## Copyright and license\r\n\r\nApache License 2.0\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnationalsecurityagency%2Ffractalrabbit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnationalsecurityagency%2Ffractalrabbit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnationalsecurityagency%2Ffractalrabbit/lists"}