SLM Lab: A Comprehensive Benchmark and Modular Software Framework for Reproducible Deep Reinforcement Learning

28 Dec 2019 Keng Wah Loon Laura Graesser Milan Cvitkovic

We introduce SLM Lab, a software framework for reproducible reinforcement learning (RL) research. SLM Lab implements a number of popular RL algorithms, provides synchronous and asynchronous parallel experiment execution, hyperparameter search, and result analysis... (read more)

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Methods used in the Paper


METHOD TYPE
ReLU
Activation Functions
Adam
Stochastic Optimization
Soft Actor Critic
Policy Gradient Methods
Entropy Regularization
Regularization
PPO
Policy Gradient Methods
A2C
Policy Gradient Methods
Experience Replay
Replay Memory
Double Q-learning
Off-Policy TD Control
Double DQN
Q-Learning Networks
Q-Learning
Off-Policy TD Control
Dense Connections
Feedforward Networks
Convolution
Convolutions
DQN
Q-Learning Networks