On-Policy Trust Region Policy Optimisation with Replay Buffers

Building upon the recent success of deep reinforcement learning methods, we investigate the possibility of on-policy reinforcement learning improvement by reusing the data from several consecutive policies. On-policy methods bring many benefits, such as ability to evaluate each resulting policy... (read more)

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Methods used in the Paper


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