Deep Reinforcement Learning for Dialogue Generation

Recent neural models of dialogue generation offer great promise for generating responses for conversational agents, but tend to be shortsighted, predicting utterances one at a time while ignoring their influence on future outcomes. Modeling the future direction of a dialogue is crucial to generating coherent, interesting dialogues, a need which led traditional NLP models of dialogue to draw on reinforcement learning. In this paper, we show how to integrate these goals, applying deep reinforcement learning to model future reward in chatbot dialogue. The model simulates dialogues between two virtual agents, using policy gradient methods to reward sequences that display three useful conversational properties: informativity (non-repetitive turns), coherence, and ease of answering (related to forward-looking function). We evaluate our model on diversity, length as well as with human judges, showing that the proposed algorithm generates more interactive responses and manages to foster a more sustained conversation in dialogue simulation. This work marks a first step towards learning a neural conversational model based on the long-term success of dialogues

Technology assessment of advanced automation for space missions

Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

Dialogue based interfaces for universal access.

Conversation provides an excellent means of communication for almost all people. Consequently, a conversational interface is an excellent mechanism for allowing people to interact with systems. Conversational systems are an active research area, but a wide range of systems can be developed with current technology. More sophisticated interfaces can take considerable effort, but simple interfaces can be developed quite rapidly. This paper gives an introduction to the current state of the art of conversational systems and interfaces. It describes a methodology for developing conversational interfaces and gives an example of an interface for a state benefits web site. The paper discusses how this interface could improve access for a wide range of people, and how further development of this interface would allow a larger range of people to use the system and give them more functionality