Learning to generate pointing gestures in situated embodied conversational agents.

ABSTRACT: One of the main goals of robotics and intelligent agent research is to enable them to communicate with humans in physically situated settings. Human communication consists of both verbal and non-verbal modes. Recent studies in enabling communication for intelligent agents have focused on verbal modes, i.e., language and speech. However, in a situated setting the non-verbal mode is crucial for an agent to adapt flexible communication strategies. In this work, we focus on learning to generate non-verbal communicative expressions in situated embodied interactive agents. Specifically, we show that an agent can learn pointing gestures in a physically simulated environment through a combination of imitation and reinforcement learning that achieves high motion naturalness and high referential acc

SUBMITTER: Deichler A 

PROVIDER: S-EPMC10097883 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature