EFFICIENT DIALOGUE POLICY LEARNING

Efficient exploration of natural language conversations associated with dialogue policy learning may be performed using probabilistic distributions. Exploration may comprise identifying key terms associated with the received natural language input utilizing the structured representation. Identifying key terms may include converting raw text of the received natural language input into a structured representation. Exploration may also comprise mapping at least one of the key terms to an action to be performed by the computer system in response to receiving natural language input associated with the at least one key term. Mapping may then be performed using a probabilistic distribution. The action may then be performed by the computer system. A replay buffer may also be utilized by the computer system to track what has occurred in previous conversations. The replay buffer may then be pre-filled with one or more successful dialogues to jumpstart exploration.