Rule Space Analysis

Rule Space Analysis is a systematic methodological framework within cellular automata research that identifies, classifies, and characterizes the global dynamical behaviors of cellular automaton rules by exhaustively exploring their rule space to reveal structural and functional relationships among rules, initial conditions, and emergent computational properties.

79

Publications

5.1K

Citations

144

Authors

83

Institutions

Publications per year

2017–2026

10

Authors

144

  1. KK
    Kikumi K. Tatsuoka

    University of Illinois Urbana-Champaign, United States

    12 publications · 1.6K citations

    11

    h-index

  2. JR
    Jennifer Rexford

    Princeton University, United States

    5 publications · 586 citations

    5

    h-index

  3. KM
    Kathleen M. Sheehan

    Educational Testing Service, United States

    4 publications · 71 citations

    4

    h-index

  4. MB
    Menucha Birenbaum

    Tel Aviv University, Israel

    4 publications · 217 citations

    4

    h-index

  5. AW
    Andrew Wuensche

    Santa Fe Institute, United States

    3 publications · 339 citations

    3

    h-index

1–5 of 144

Venues

  1. ETS Research Report Series

    4 publications · 71 citations

    4

    h-index

  2. International Journal of Bifurcation and Chaos

    IJBC · 4 publications · 80 citations

    4

    h-index

  3. Complexity

    4 publications · 214 citations

    4

    h-index

  4. Physica D Nonlinear Phenomena

    3 publications · 232 citations

    3

    h-index

  5. Journal of Educational Measurement

    2 publications · 999 citations

    2

    h-index

1–5