Concepedia

Risk-sensitive Reinforcement Learning

Risk-Sensitive Reinforcement Learning is a framework within reinforcement learning that extends standard Markov decision processes by incorporating sensitivity to the variability and uncertainty of returns, thereby optimizing policies based on risk-aware criteria rather than expected cumulative reward alone.

70

Publications

6.1K

Citations

201

Authors

105

Institutions

Publications per year

2017–2026

43

Variants

Risk-aware Reinforcement Learning

Parents

Publications

70

A comprehensive survey on safe reinforcement learning

Javier García, Fernando Fernández · Journal of Machine Learning Research · 2015 · 1.2K citations

, , +16

Neural Prediction Errors Reveal a Risk-Sensitive Reinforcement-Learning Process in the Human Brain

Yael Niv, Jeffrey A. Edlund, Peter Dayan et al. · Journal of Neuroscience · 2012 · 404 citations · Full text

, , +17

Deep Reinforcement Learning for Delay-Oriented IoT Task Scheduling in SAGIN

Conghao Zhou, Wen Wu, Hongli He et al. · IEEE Transactions on Wireless Communications · 2020 · 319 citations

, , +16

Performance functions and reinforcement learning for trading systems and portfolios

John Moody, Lizhong Wu, Yuansong Liao et al. · Journal of Forecasting · 1998 · 293 citations

, , +13

Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness

Guofa Li, Yifan Yang, Shen Li et al. · Transportation Research Part C Emerging Technologies · 2021 · 286 citations

, , +17

1–5 of 70

Authors

201

  1. LA
    L. A. Prashanth

    Indian Institute of Science Bangalore, India

    5 publications · 128 citations

    5

    h-index

  2. MC
    Michael C. Fu

    University of Maryland, College Park, United States

    4 publications · 113 citations

    4

    h-index

  3. SM
    Shie Mannor

    Technion – Israel Institute of Technology, Israel

    3 publications · 207 citations

    3

    h-index

  4. VS
    Vivek S. Borkar

    Tata Institute of Fundamental Research, India

    3 publications · 112 citations

    3

    h-index

  5. ZZ
    Zhengyuan Zhou

    Stanford University, United States

    3 publications · 61 citations

    3

    h-index

1–5 of 201

Institutions

105

  1. Princeton University

    Princeton, United States

    4 h-index

    5 publications

    458 citations

  2. University of California, Berkeley

    Berkeley, United States

    4 h-index

    7 publications

    112 citations

  3. Stanford University

    Stanford, United States

    4 h-index

    5 publications

    174 citations

  4. Technion – Israel Institute of Technology

    Haifa, Israel

    3 h-index

    7 publications

    551 citations

  5. Tsinghua University

    Beijing, China

    3 h-index

    18 publications

    1.5K citations

  6. Google (United States)

    Mountain View, United States

    3 h-index

    11 publications

    475 citations

  7. University of Toronto

    Toronto, Canada

    3 h-index

    6 publications

    138 citations

  8. Technische Universität Berlin

    Berlin, Germany

    2 h-index

    2 publications

    308 citations

1–8 of 105

Venues

  1. arXiv (Cornell University)

    Repository · 17 publications · 832 citations

    14

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 105 citations

    3

    h-index

  3. Neural Computation

    2 publications · 296 citations

    2

    h-index

  4. Journal of Forecasting

    2 publications · 353 citations

    2

    h-index

  5. Artificial Intelligence

    2 publications · 63 citations

    2

    h-index

1–5