Cheng Chang

Agent-Aware Dropout DQN for Safe and Efficient On-line Dialogue Policy Learning

2017

Hand-crafted rules and reinforcement learning (RL) are two popular choices to obtain dialogue policy. The rule-based policy is often reliable within predefined scope but not self-adaptable, whereas RL is evolvable with data but often suffers …