Deep Q-Learning with Q-Matrix Transfer Learning for Novel Fire Evacuation Environment

We focus on the important problem of emergency evacuation, which clearly could benefit from reinforcement learning that has been largely unaddressed. Emergency evacuation is a complex task which is difficult to solve with reinforcement learning, since an emergency situation is highly dynamic, with a lot of changing variables and complex constraints that makes it difficult to train on... (read more)

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Methods used in the Paper


METHOD TYPE
Sarsa
On-Policy TD Control
Entropy Regularization
Regularization
PPO
Policy Gradient Methods
A2C
Policy Gradient Methods
Dense Connections
Feedforward Networks
Convolution
Convolutions
Q-Learning
Off-Policy TD Control
DQN
Q-Learning Networks