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  • [2108. 10403] Robust Risk-Aware Reinforcement Learning - arXiv. org
    We present a reinforcement learning (RL) approach for robust optimisation of risk-aware performance criteria To allow agents to express a wide variety of risk-reward profiles, we assess the value of a policy using rank dependent expected utility (RDEU)
  • Robust Risk-Aware Reinforcement Learning | SIAM Journal on Financial . . .
    We present a reinforcement learning (RL) approach for robust optimization of risk-aware performance criteria To allow agents to express a wide variety of risk-reward profiles, we assess the value of a policy using rank dependent expected utility (RDEU)
  • Robust Risk-Aware Reinforcement Learning - SSRN
    develop a reinforcement learning (RL) approach for solving a general class of robust stochastic optimisation problems, where agents aim to minimise their risk – measured by RDEU – subject to model uncertainty, and thus robustifying their actions
  • Some implementations from the paper robust risk aware reinforcement . . .
    Robust Risk-Aware Reinforcement Learning by Sebastian Jaimungal, Silvana Pesenti, Ye Sheng Wang, and Hariom Tatsat https: arxiv org abs 2108 10403 The * ipynb here implement three example problems solved using the approach in the paper: Robust static portfolio allocation; Beating a benchmark; Robust Statistical Arbitrage
  • Confidence-aware Robust Dynamical Distance Constrained Reinforcement . . .
    Navigating in a crowded social environment without collisions or freezing is a crucial and challenging task Recent studies have demonstrated considerable success using Deep Reinforcement Learning for social robot navigation However, the lack of safety guarantees remains a prevalent problem among these methods To address this limitation, we present a comprehensive safety framework that
  • Robust Risk-Aware Reinforcement Learning | SIAM Journal on Financial . . .
    We present a reinforcement learning (RL) approach for robust optimization of risk-aware performance criteria To allow agents to express a wide variety of risk-reward profiles, we assess the value of a policy using rank dependent expected utility (RDEU)
  • [2309. 14246] Learning Risk-Aware Quadrupedal Locomotion using . . .
    In this work, we propose a risk sensitive locomotion training method employing distributional reinforcement learning to consider safety explicitly Instead of relying on a value expectation, we estimate the complete value distribution to account for uncertainty in the robot's interaction with the environment
  • Risk Aware Reinforcement Learning - TU Darmstadt
    Motivations Taxonomy Quick Reinforcement Learning Reminder Worst Case Criterion Risk Sensitivity Robust MDP Q^-Learning (Heger 1994) Direct minimization of the worst case : Q(s;a) := minfQ(s;a);r + max a0 Q(s0;a0)g The idea is to maintain the memory of the worst sample observed Note that no learning rate is required Too pessimistic;
  • Robust Risk-Aware Reinforcement Learning - ResearchGate
    We present a reinforcement learning (RL) approach for robust optimisation of risk-aware performance criteria To allow agents to express a wide variety of risk-reward profiles, we assess the
  • GitHub - SafeRL-Lab Robust-RL-Baselines: Robust Reinforcement Learning . . .
    Robust Reinforcement Learning Benchmark Contribute to SafeRL-Lab Robust-RL-Baselines development by creating an account on GitHub





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