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The variance of discounted Markov decision processes

https://doi.org/10.1017/s0021900200023123
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Finite Markov Chains.

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Risk-Averse Trust Region Optimization for Reward-Volatility Reduction
inferred← citeshttps://doi.org/10.24963/ijcai.2023/784openalex-snapshot
Mean-Semivariance Policy Optimization via Risk-Averse Reinforcement Learning (Extended Abstract)
inferred← citeshttps://doi.org/10.2514/6.2025-2793openalex-snapshot
Uncertainty-Driven Distributional Reinforcement Learning for Flight Control
inferred← citeshttps://doi.org/10.3934/math.20231455openalex-snapshot
The optimal probability of the risk for finite horizon partially observable Markov decision processes
inferred← citeshttps://doi.org/10.4230/lipics.fsttcs.2013.487openalex-snapshot
Solvency Markov Decision Processes with Interest
inferred← citeshttps://doi.org/10.48550/arxiv.1104.5601openalex-snapshot
Mean-Variance Optimization in Markov Decision Processes
inferred← citeshttps://doi.org/10.48550/arxiv.1202.3890openalex-snapshot
PAC Bounds for Discounted MDPs
inferred← citeshttps://doi.org/10.48550/arxiv.1206.6404openalex-snapshot
Policy Gradients with Variance Related Risk Criteria
inferred← citeshttps://doi.org/10.48550/arxiv.1206.6461openalex-snapshot
On the Sample Complexity of Reinforcement Learning with a Generative Model
inferred← citeshttps://doi.org/10.48550/arxiv.1403.3321openalex-snapshot
On Average Risk-sensitive Markov Control Processes
inferred← citeshttps://doi.org/10.48550/arxiv.1406.3339openalex-snapshot
Algorithms for CVaR Optimization in MDPs
inferred← citeshttps://doi.org/10.48550/arxiv.1506.02188openalex-snapshot
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach
inferred← citeshttps://doi.org/10.48550/arxiv.1510.08906openalex-snapshot
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1607.00446openalex-snapshot
A Greedy Approach to Adapting the Trace Parameter for Temporal Difference Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1707.06887openalex-snapshot
A Distributional Perspective on Reinforcement Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1709.05380openalex-snapshot
The Uncertainty Bellman Equation and Exploration
inferred← citeshttps://doi.org/10.48550/arxiv.1711.10789openalex-snapshot
Efficient exploration with Double Uncertain Value Networks
inferred← citeshttps://doi.org/10.48550/arxiv.1804.08617openalex-snapshot
Distributed Distributional Deterministic Policy Gradients
inferred← citeshttps://doi.org/10.48550/arxiv.1806.01584openalex-snapshot
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1806.04242openalex-snapshot
The Potential of the Return Distribution for Exploration in RL
inferred← citeshttps://doi.org/10.48550/arxiv.1806.06923openalex-snapshot
Implicit Quantile Networks for Distributional Reinforcement Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1806.07857openalex-snapshot
RUDDER: Return Decomposition for Delayed Rewards
inferred← citeshttps://doi.org/10.48550/arxiv.1807.09647openalex-snapshot
Variational Bayesian Reinforcement Learning with Regret Bounds
inferred← citeshttps://doi.org/10.48550/arxiv.1904.11392openalex-snapshot
Continuous-Time Mean-Variance Portfolio Selection: A Reinforcement Learning Framework
inferred← citeshttps://doi.org/10.48550/arxiv.1905.09638openalex-snapshot
Estimating Risk and Uncertainty in Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1906.03393openalex-snapshot
Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling
inferred← citeshttps://doi.org/10.48550/arxiv.1907.04269openalex-snapshot
A Scheme for Dynamic Risk-Sensitive Sequential Decision Making
inferred← citeshttps://doi.org/10.48550/arxiv.1907.04651openalex-snapshot
Incrementally Learning Functions of the Return
inferred← citeshttps://doi.org/10.48550/arxiv.1908.08379openalex-snapshot
Practical Risk Measures in Reinforcement Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1911.03618openalex-snapshot
Worst Cases Policy Gradients
inferred← citeshttps://doi.org/10.48550/arxiv.2006.05591openalex-snapshot
Adaptive Experimental Design with Temporal Interference: A Maximum Likelihood Approach
inferred← citeshttps://doi.org/10.48550/arxiv.2006.12686openalex-snapshot
Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty
inferred← citeshttps://doi.org/10.48550/arxiv.2011.04185openalex-snapshot
Robust Batch Policy Learning in Markov Decision Processes
inferred← citeshttps://doi.org/10.48550/arxiv.2012.14098openalex-snapshot
Risk-Sensitive Deep RL: Variance-Constrained Actor-Critic Provably Finds Globally Optimal Policy
inferred← citeshttps://doi.org/10.48550/arxiv.2102.05762openalex-snapshot
Risk-Averse Bayes-Adaptive Reinforcement Learning
inferred← citeshttps://doi.org/10.48550/arxiv.2103.06224openalex-snapshot
An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning
inferred← citeshttps://doi.org/10.48550/arxiv.2104.12820openalex-snapshot
Universal Off-Policy Evaluation
inferred← citeshttps://doi.org/10.48550/arxiv.2107.02711openalex-snapshot
A Unified Off-Policy Evaluation Approach for General Value Function
inferred← citeshttps://doi.org/10.48550/arxiv.cs/0301006openalex-snapshot
Temporal plannability by variance of the episode length
inferred← citeshttps://doi.org/10.5109/13455openalex-snapshot
A UTILITY DEVIATION IN DISCOUNTED MARKOV DECISION PROCESSES WITH GENERAL UTILITY
inferred← citeshttps://doi.org/10.5109/13494openalex-snapshot
NUMERICAL ENCLOSURE FOR THE OPTIMAL THRESHOLD PROBABILITY IN DISCOUNTED MARKOV DECISION PROCESSES
inferred← citeshttps://doi.org/10.5220/0008175604120423openalex-snapshot
Risk-averse Distributional Reinforcement Learning: A CVaR Optimization Approach
inferred← citeshttps://doi.org/10.5555/2936924.2937006openalex-snapshot
A Greedy Approach to Adapting the Trace Parameter for Temporal Difference Learning
inferred← citeshttps://doi.org/10.5555/2946645.2946658openalex-snapshot
Learning the variance of the reward-to-go
inferred← citeshttps://doi.org/10.5753/eniac.2018.4431openalex-snapshot
Analysis of the Risk Sensitive Value Iteration Algorithm
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