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  聽Special issue on approximate dynamic programming and reinforcement learning
 

Editorial: Special issue on approximate dynamic programming and reinforcement learning--Silvia Ferrari,Jagannathan Sarangapani and Frank L. Lewis

 

Approximate policy iteration: a survey and some new methods--Dimitri P. BERTSEKAS

 

A review of stochastic algorithms with continuous value function approximation and some new approximate policy iteration algorithms for multidimensional continuous applications--Warren B. POWELL and Jun MA

 

Adaptive dynamic programming for online solution of a zero-sum differential game--Draguna VRABIE and Frank LEWIS

 

Approximate dynamic programming solutions with a single network adaptive critic for a class of nonlinear systems--Jie DING and S. N. BALAKRISHNAN

 

Finite horizon optimal control of discrete-time nonlinear systems with unfixed initial state using adaptive dynamic programming--Qinglai WEI and Derong LIU

 

A model-based approximate λ-policy iteration approach to online evasive path planning and the video game Ms. Pac-Man--Greg FODERARO,Vikram RAJU and Silvia FERRARI

 

Asymptotic tracking by a reinforcement learning-based adaptive critic controller--Shubhendu BHASIN,Nitin SHARMA,Parag PATRE and Warren DIXON

 

Stable reinforcement learning with recurrent neural networks--James Nate KNIGHT and Charles ANDERSON

 

Semi-Markov adaptive critic heuristics with application to airline revenue management--Ketaki KULKARNI,Abhijit GOSAVI,Susan MURRAY and Katie GRANTHAM

 

Multiresolution state-space discretization for Q-Learning with pseudorandomized discretization--Amanda LAMPTON,John VALASEK and Mrinal KUMAR

 

Hierarchical state-abstracted and socially augmented Q-Learning for reducing complexity in agent-based learning--Xueqing SUN,Tao MAO,Laura RAY,Dongqing SHI and Jerald KRALIK

 

Moving least-squares approximations for linearly-solvable stochastic optimal control problems--Mingyuan ZHONG and Emanuel TODOROV

 

Online optimal control of nonlinear discrete-time systems using approximate dynamic programming--Travis DIERKS and Sarangapani JAGANNATHAN

 
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