IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks

ICLR 2020 • Michael Luo • Jiahao Yao • Richard Liaw • Eric Liang • Ion Stoica

The practical usage of reinforcement learning agents is often bottlenecked by the duration of training time. To accelerate training, practitioners often turn to distributed reinforcement learning architectures to parallelize and accelerate the training process... (read more)

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METHOD	TYPE
Sigmoid Activation	Activation Functions
Tanh Activation	Activation Functions
PPO	Policy Gradient Methods
V-trace	Value Function Estimation
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
IMPALA	Policy Gradient Methods

METHOD

TYPE

Sigmoid Activation