The goal of this micro-project is to develop a cognitive architecture able to generate proactive communicative behaviors during human-robot interactions. The general idea is to provide information to humans which may help them to achieve desired outcomes, or to prevent possible undesired ones. Our work proposes a framework that generates and selects among opportunities for acting based on recognizing human intention, predicting environment changes, and reasoning about what is desirable in general. Our framework has two main modules to initiate proactive behavior; intention recognition and equilibrium maintenance.

Main achievements:

• Integration of two systems: user intention recognition and equilibrium maintenance in a generic architecture
• Showing stability of the architecture to many users
• Reasoning mechanism and 2nd order perspective awareness

The next steps will aim to show knowledge repair, prevent outcomes of lack of knowledge and improve trustability, transparency and legibility (user study)

Tangible outputs:

• Sera Buyukgoz, Jasmin Grosinger, Mohamed Chetouani, Alessandro Saffiotti. "Two ways to make your robot proactive: reasoning about human intentions, or reasoning about possible futures". arXiv:2205.05492 [cs.AI] 2022. DOI: 10.48550/ARXIV.2205.05492