The following pages link to Approxrl (Q26214):
Displaying 37 items.
- Batch mode reinforcement learning based on the synthesis of artificial trajectories (Q378762) (← links)
- Robust adaptive dynamic programming for linear and nonlinear systems: an overview (Q397504) (← links)
- Dynamic treatment regimes: technical challenges and applications (Q405345) (← links)
- Stochastic optimal control of unknown linear networked control system in the presence of random delays and packet losses (Q445115) (← links)
- Q-learning for continuous-time linear systems: A model-free infinite horizon optimal control approach (Q511735) (← links)
- Model-free event-triggered control algorithm for continuous-time linear systems with optimal performance (Q680566) (← links)
- Proximal algorithms and temporal difference methods for solving fixed point problems (Q721950) (← links)
- Non-zero sum Nash Q-learning for unknown deterministic continuous-time linear systems (Q900691) (← links)
- Reinforcement learning algorithms with function approximation: recent advances and applications (Q903601) (← links)
- Active network management for electrical distribution systems: problem formulation, benchmark, and approximate solution (Q1642966) (← links)
- A unified framework for stochastic optimization (Q1719609) (← links)
- Decentralized reinforcement learning of robot behaviors (Q1748471) (← links)
- Reinforcement learning endowed with safe veto policies to learn the control of linked-multicomponent robotic systems (Q1749908) (← links)
- Error bounds for constant step-size \(Q\)-learning (Q1932736) (← links)
- A linear programming methodology for approximate dynamic programming (Q2023646) (← links)
- A deep reinforcement learning framework for continuous intraday market bidding (Q2071376) (← links)
- A Markov decision process for response-adaptive randomization in clinical trials (Q2101385) (← links)
- Predictive market making via machine learning (Q2120114) (← links)
- An overview on recent machine learning techniques for port Hamiltonian systems (Q2127392) (← links)
- Self-triggered control of probabilistic Boolean control networks: a reinforcement learning approach (Q2159969) (← links)
- Finding multiple Nash equilibria via machine learning-supported Gröbner bases (Q2178154) (← links)
- Fitted Q-iteration by functional networks for control problems (Q2293779) (← links)
- Adaptive cruise control via adaptive dynamic programming with experience replay (Q2318252) (← links)
- Approximate dynamic programming for stochastic \(N\)-stage optimization with application to optimal consumption under uncertainty (Q2450902) (← links)
- A systematic study on meta-heuristic approaches for solving the graph coloring problem (Q2664279) (← links)
- On the effect of probing noise in optimal control LQR via Q-learning using adaptive filtering algorithms (Q2673621) (← links)
- A lexicographic approach to constrained MDP admission control (Q2792714) (← links)
- Optimized look-ahead tree policies: a bridge between look-ahead tree policies and direct policy search (Q2795793) (← links)
- Adaptive critic design with graph Laplacian for online learning control of nonlinear systems (Q2795795) (← links)
- Chaotic dynamics and convergence analysis of temporal difference algorithms with bang-bang control (Q2800471) (← links)
- Design and comparison base analysis of adaptive estimator for completely unknown linear systems in the presence of OE noise and constant input time delay (Q2828544) (← links)
- Approximate policy iteration: a survey and some new methods (Q2887629) (← links)
- A review of stochastic algorithms with continuous value function approximation and some new approximate policy iteration algorithms for multidimensional continuous applications (Q2887630) (← links)
- Event-triggered optimal tracking control of nonlinear systems (Q2965287) (← links)
- Bayesian Exploration for Approximate Dynamic Programming (Q4971589) (← links)
- Data-driven adaptive dynamic programming for partially observable nonzero-sum games via <i>Q</i>-learning method (Q5025895) (← links)
- Population based optimization via differential evolution and adaptive fractional gradient descent (Q5082451) (← links)
