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In this paper, we consider risk-sensitive sequential decision-making in Reinforcement Learning (RL).
Risk-sensitive markov decision processes
Ronald A Howard and James E Matheson · 1972
Earlier work this paper cites.
Markovian decision processes with uncertain transition probabilities
Roy E. Lave Jay K. Satia · 1973
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The bootstrap method for assessing statistical accuracy
Bradley Efron and Robert Tibshirani · 1985
Earlier work this paper cites.
Q-learning
Christopher JCH Watkins and Peter Dayan · 1992
Earlier work this paper cites.
Consideration of risk in reinforcement learning
Matthias Heger · 1994
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Risk sensitive markov decision processes
Steven I Marcus, Emmanual Fernández-Gaucherand, Daniel Hernández-Hernandez, Stefano Coraluppi, and Pedram Fard · 1997
Earlier work this paper cites.
Axiomatic characterization of insurance prices
Shaun S. Wang, Virginia R. Young, and Harry H. Panjer · 1997
Earlier work this paper cites.
Coherent measures of risk
Philippe Artzner, Freddy Delbaen, Jean-Marc Eber, and David Heath · 1999
Earlier work this paper cites.
Risk-sensitive and minimax control of discrete-time, finite-state markov decision processes
Stefano P Coraluppi and Steven I Marcus · 1999
Earlier work this paper cites.
Optimization of conditional value-at-risk
R Tyrrell Rockafellar, Stanislav Uryasev, et al · 2000
Earlier work this paper cites.
Distortion risk measures: Coherence and stochastic dominance
Julia L Wirch and Mary R Hardy · 2001
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O. Mihatsch and R. Neuneier · 2002
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Giorgio Szegö · 2002
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A risk measure that goes beyond coherence
S. Wang · 2002
Earlier work this paper cites.
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Nicolo Cesa-Bianchi and Gábor Lugosi · 2006
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Christos Dimitrakakis · 2006
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Ensembles for sequence learning
Christos Dimitrakakis · 2007
Earlier work this paper cites.
Ensemble algorithms in reinforcement learning
Marco A Wiering and Hado Van Hasselt · 2008
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Yongsheng Song and Jia-An Yan · 2009
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Risk-averse dynamic programming for markov decision processes
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Entropic value-at-risk: A new coherent risk measure
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Decomposition of uncertainty in bayesian deep learning for efficient and risk-sensitive learning
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Epistemic risk-sensitive reinforcement learning
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