Implementable Decision Making

Implementable Decision Making is a decision-making framework within autonomous agricultural systems that integrates real-time data processing, predictive modeling, and operational constraints to generate actionable, context-aware control strategies specifically for the deployment of autonomous tractors in dynamic farming environments.

57

Publications

3.3K

Citations

149

Authors

93

Institutions

Publications per year

2017–2026

12

Authors

149

  1. AM
    Alexandra M. Newman

    Colorado School of Mines, United States

    2 publications · 104 citations

    2

    h-index

  2. ID
    Izak Duenyas

    University of Michigan, United States

    2 publications · 189 citations

    2

    h-index

  3. TB
    Trond Bjørndal

    Norwegian School of Economics, Norway

    2 publications · 104 citations

    2

    h-index

  4. CW
    Clark W. Gellings

    Electric Power Research Institute, United States

    2 publications · 169 citations

    2

    h-index

  5. SM
    Seyed M. R. Iravani

    Northwestern University, United States

    2 publications · 189 citations

    2

    h-index

1–5 of 149

Venues

  1. IIE Transactions

    3 publications · 234 citations

    3

    h-index

  2. 2

    h-index

  3. Operations Research

    2 publications · 37 citations

    2

    h-index

  4. Econometrica

    2 publications · 573 citations

    2

    h-index

  5. Agricultural Economics

    2 publications · 222 citations

    2

    h-index

1–5