This research shed the light on how humans interact with virtual partners (Figure 1; 3D view: https://p3d.in/bVJpq) in an interactive environment based on economic games and how this environment can be applied to the training process with immersive technologies. The designed system could be integrated as a tool and be a component of an e-learning platform with Conversational AI and human-agent-interactions which allows human users to play and learn. Scientifically, we have considered the trust problem from a different point of view-learning by doing (i.e., gaming), and proposed that individuals can wear "trust care"lenses on trained "golden eyes"while communicating with others. We explore how contextual trust can be used to promote any human-agent collaboration even in the domain of a competitive negotiation scenario. We present small-scale online testing via instant messaging in Telegram [@trudicbot] and prepare VR testing to demonstrate the potentials of the trust-based game approach.
CITATION STYLE
Vlasov, A. V., Zinchenko, O. O., Zhao, Z., Bakaev, M., & Karavaev, A. (2021). The Design of a Trust-based Game as a Conversational Component of Interactive Environment for a Human-agent Negotiation. In MuCAI 2021 - Proceedings of the 2nd ACM Multimedia Workshop on Multimodal Conversational AI, co-located with ACM MM 2021 (pp. 19–23). Association for Computing Machinery, Inc. https://doi.org/10.1145/3475959.3485393
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