A Self-Tuning Actor-Critic Algorithm

Reinforcement learning algorithms are highly sensitive to the choice of hyperparameters, typically requiring significant manual effort to identify hyperparameters that perform well on a new domain. In this paper, we take a step towards addressing this issue by using metagradients to automatically adapt hyperparameters online by meta-gradient descent (Xu et al., 2018)... (read more)

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METHOD	TYPE
Sigmoid Activation	Activation Functions
Tanh Activation	Activation Functions
Experience Replay	Replay Memory
Entropy Regularization	Regularization
Residual Connection	Skip Connections
Gradient Clipping	Optimization
RMSProp	Stochastic Optimization
ReLU	Activation Functions
Max Pooling	Pooling Operations
Convolution	Convolutions
LSTM	Recurrent Neural Networks
V-trace	Value Function Estimation
IMPALA	Policy Gradient Methods

METHOD

TYPE

Sigmoid Activation