Multi-objective Markov Decision Processes

Multi-Objective Markov Decision Processes is a sequential decision-making framework in which a single agent seeks to optimize multiple conflicting objectives simultaneously under uncertainty, distinguished from single-objective variants by the presence of a vector-valued reward function that necessitates trade-offs among objectives.

121

Publications

5.5K

Citations

399

Authors

160

Institutions

Publications per year

2017–2026

66

Authors

399

  1. MR
    Marcello Restelli

    Politecnico di Milano, Italy

    5 publications · 192 citations

    5

    h-index

  2. KC
    Krishnendu Chatterjee

    Institute of Science and Technology Austria, Austria

    5 publications · 183 citations

    5

    h-index

  3. AK
    Antonı́n Kučera

    Masaryk University, Czechia

    3 publications · 133 citations

    3

    h-index

  4. AC
    Andrea Castelletti

    Politecnico di Milano, Italy

    3 publications · 79 citations

    3

    h-index

  5. MP
    Matteo Pirotta

    Politecnico di Milano, Italy

    3 publications · 127 citations

    3

    h-index

1–5 of 399

Venues

  1. IEEE Internet of Things Journal

    5 publications · 322 citations

    5

    h-index

  2. arXiv (Cornell University)

    Repository · 4 publications · 97 citations

    4

    h-index

  3. Neurocomputing

    3 publications · 103 citations

    3

    h-index

  4. Expert Systems with Applications

    3 publications · 106 citations

    3

    h-index

  5. Applied Soft Computing

    3 publications · 152 citations

    3

    h-index

1–5