Shaping a social robot’s humor with Natural Language Generation and socially-aware reinforcement learning

摘要

Humor is an important aspect in human interaction to regulate conversations, increase interpersonal attraction and trust. For social robots, humor is one aspect to make interactions more natural, enjoyable, and to increase credibility and acceptance. In combination with appropriate non-verbal behavior, natural language generation offers the ability to create content on-the-fly. This work outlines the building-blocks for providing an individual, multimodal interaction experience by shaping the robot's humor with the help of Natural Language Generation and Reinforcement Learning based on human social signals.