Iterative Policy Learning

Iterative Policy Learning is a methodological framework within public sector experimentation that systematically refines policy interventions through successive cycles of design, implementation, evaluation, and adaptation based on empirical feedback.

49

Publications

3.3K

Citations

133

Authors

67

Institutions

Publications per year

2017–2026

17

Authors

133

  1. JX
    Jian‐Xin Xu

    National University of Singapore, Singapore

    3 publications · 219 citations

    3

    h-index

  2. DH
    Deqing Huang

    Southwest Jiaotong University, China

    3 publications · 80 citations

    3

    h-index

  3. IL
    Ian Lane

    Carnegie Mellon University, United States

    2 publications · 108 citations

    2

    h-index

  4. ZY
    Zhuoran Yang

    Princeton University, United States

    2 publications · 325 citations

    2

    h-index

  5. ZW
    Zhaoran Wang

    Princeton University, United States

    2 publications · 325 citations

    2

    h-index

1–5 of 133

Venues

  1. Automatica

    4 publications · 462 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 145 citations

    2

    h-index

  3. IFAC Proceedings Volumes

    2 publications · 25 citations

    2

    h-index

  4. Journal of the Franklin Institute

    1 publications · 18 citations

    1

    h-index

  5. Housing Policy Debate

    1 publications · 98 citations

    1

    h-index

1–5