Model-free Legibility: Enhancing Human-Robot Interactions through Implicit Communication and Influence Modulation
<|reference_start|>Model-free Legibility: Enhancing Human-Robot Interactions through Implicit Communication and Influence Modulation: Communication is essential for successful interaction. In human-robot interaction, implicit communication enhances robots' understanding of human needs, emotions, and intentions. This paper introduces a method to foster implicit communication in HRI without explicitly modeling human intentions or relying on pre-existing knowledge. Leveraging Transfer Entropy, we modulate influence between agents in social interactions in scenarios involving either collaboration or competition. By integrating influence into agents' rewards within a partially observable Markov decision process, we demonstrate that boosting influence enhances collaboration or competition performance, while resisting influence diminishes performance. Our findings are validated through simulations and real-world experiments with human participants.<|reference_end|>
@article{jiang2024model-free,
    title={Model-free Legibility: Enhancing Human-Robot Interactions through
  Implicit Communication and Influence Modulation},
    author={Haoyang Jiang, Elizabeth A. Croft, Michael G. Burke},
    journal={arXiv preprint arXiv:2406.12253},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.12253},
    primaryClass={cs.RO}
}