Pages that link to "Item:Q1870312"
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The following pages link to Approximate gradient methods in policy-space optimization of Markov reward processes (Q1870312):
Displaying 16 items.
- Modeling and optimization of a product-service system with additional service capacity and impatient customers (Q336407) (← links)
- Analysis and improvement of policy gradient estimation (Q448295) (← links)
- Simulation-based optimization of Markov decision processes: an empirical process theory approach (Q608432) (← links)
- Estimation and approximation bounds for gradient-based reinforcement learning (Q1604222) (← links)
- A basic formula for performance gradient estimation of semi-Markov decision processes (Q2253434) (← links)
- Regularized policy iteration with nonparametric function spaces (Q2834459) (← links)
- Using Gaussian processes for variance reduction in policy gradient algorithms (Q2908998) (← links)
- Bias and Variance Approximation in Value Function Estimates (Q3116079) (← links)
- Environment-driven distributed evolutionary adaptation in a population of autonomous robotic agents (Q3168239) (← links)
- The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning (Q4943730) (← links)
- Deep Reinforcement Learning: A State-of-the-Art Walkthrough (Q5145831) (← links)
- Parametric Approximation Policy Iteration Algorithm Based on Gaussian Process (Q5165995) (← links)
- Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning (Q5189863) (← links)
- Approximation of average cost Markov decision processes using empirical distributions and concentration inequalities (Q5265786) (← links)
- Parallel Nonstationary Direct Policy Search for Risk-Averse Stochastic Optimization (Q5364280) (← links)
- On-line policy gradient estimation with multi-step sampling (Q5962027) (← links)
