… policy is depended on a probability distribution. In this paper, a novel fuzzy deterministic policy
… The novel proposed algorithm is based on the deterministic policy gradient theorem and …

… To implement higher tracking accuracy for the maneuvering target tracking, many improved
… the deep deterministic policy gradient method in solving maneuver target tracking problems …

… Methods: In this paper, a deep deterministic policy gradient–nonlinear nonsingular fast
terminal sliding mode control (DDPG–NNFTSMC) strategy is proposed for industrial robot control. …

… deterministic policy gradient (DDPG) algorithm so that the steering system can execute the
desired steering angle more quickly and more accurately. Simulation results demonstrate that …

… An adaptive proportional integral robust (PIR) control method based on deep deterministic
policy gradient (DDPGPIR) is proposed for n-link robotic manipulator systems with model …

… Therefore, this paper proposes a reward-adaptive control method for wind power tracking
based on Deep Deterministic Policy Gradient (DDPG). The method can use one controller to …

… algorithms with three popular RL baselines: deep deterministic policy gradient (MUDDPG)
[35], twin delayed MUDDPG (MUTD3) [36] and proximal policy optimization (MUPPO2) [37]. …

… Minimizing this error is of the utmost interest in target … policy builds on an automated
perception module which produces a target track and on an acoustic model to estimate the target …

… This study proposes a Deep Deterministic Policy Gradient algorithm based on optimized
sample pools and average motion critic network (OSAM-DDPG) to realize the path following …

… the deterministic policies can also achieve a sample complexity of O(ϵ−2). For the off-policy …
[2021], which causes substantial difference in our analysis besides the deterministic policy. …