Package: datafsm Title: Estimating Finite State Machine Models from Data Version: 0.2.5 Date: 2025-11-14 Authors@R: c(person(given = c("John", "J."), family = "Nay", email = "john.j.nay@gmail.com", role = "aut"), person(given = c("Jonathan", "M."), family = "Gilligan", email = "jonathan.gilligan@vanderbilt.edu", comment = c(ORCID = "0000-0003-1375-6686"), role = c("cre", "aut"))) Description: Automatic generation of finite state machine models of dynamic decision-making that both have strong predictive power and are interpretable in human terms. We use an efficient model representation and a genetic algorithm-based estimation process to generate simple deterministic approximations that explain most of the structure of complex stochastic processes. We have applied the software to empirical data, and demonstrated it's ability to recover known data-generating processes by simulating data with agent-based models and correctly deriving the underlying decision models for multiple agent models and degrees of stochasticity. URL: https://jonathan-g.github.io/datafsm/, https://github.com/jonathan-g/datafsm BugReports: https://github.com/jonathan-g/datafsm/issues Depends: R (>= 4.0), methods (>= 4.0), stats (>= 4.0) License: MIT + file LICENSE LazyData: true LinkingTo: Rcpp (>= 1.0) Suggests: doParallel (>= 1.0), foreach (>= 1.5), testthat (>= 3.0), diagram (>= 1.6), knitr (>= 1.33), rmarkdown (>= 2.8), pander (>= 0.6), dplyr (>= 1.0), tidyr (>= 1.0), purrr (>= 0.3) Imports: caret (>= 6.0), GA (>= 3.2), Rcpp (>= 1.0) VignetteBuilder: knitr RoxygenNote: 7.3.3 Encoding: UTF-8 Language: en-US Config/pak/sysreqs: libicu-dev Repository: https://j-magnolia.r-universe.dev Date/Publication: 2025-12-01 22:31:08 UTC RemoteUrl: https://github.com/j-magnolia/datafsm RemoteRef: HEAD RemoteSha: 099f308daecbba7a6423eea5e389d518169a74df NeedsCompilation: yes Packaged: 2026-09-23 07:41:07 UTC; root Author: John J. Nay [aut], Jonathan M. Gilligan [cre, aut] (ORCID: ) Maintainer: Jonathan M. Gilligan