Incremental Reinforcement Learning --- a New Continuous Reinforcement Learning Frame Based on Stochastic Differential Equation methods

8 Aug 2019 Tianhao Chen Limei Cheng Yang Liu Wenchuan Jia Shugen Ma

Continuous reinforcement learning such as DDPG and A3C are widely used in robot control and autonomous driving. However, both methods have theoretical weaknesses... (read more)

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Methods used in the Paper


METHOD TYPE
Experience Replay
Replay Memory
Entropy Regularization
Regularization
Dense Connections
Feedforward Networks
Weight Decay
Regularization
ReLU
Activation Functions
Adam
Stochastic Optimization
Softmax
Output Functions
Convolution
Convolutions
Batch Normalization
Normalization
DDPG
Policy Gradient Methods
A3C
Policy Gradient Methods