Trust model of privacy-concerned, emotionally-aware agents in a cooperative logistics problem
This work addresses privacy and emotional trust in cooperative logistics for mixed human-vehicle environments, but it is incremental as it builds on existing BDI and cognitive modeling paradigms.
The authors tackled the problem of modeling trust and emotions in cooperative logistics involving humans and unmanned vehicles, resulting in simulations that showed improved agent performance in time savings and privacy protection.
In this paper we propose a trust model to be used into a hypothetical mixed environment where humans and unmanned vehicles cooperate. We address the inclusion of emotions inside a trust model in a coherent way to the practical approaches to the current psychology theories. The most innovative contribution is how privacy issues play a role in the cooperation decisions of the emotional trust model. Both, emotions and trust have been cognitively modeled and managed with the Beliefs, Desires and Intentions (BDI) paradigm into autonomous agents implemented in GAML (the programming language of GAMA agent platform) that communicates using the IEEE FIPA standard. The trusting behaviour of these emotional agents is tested in a cooperative logistics problem where: agents have to move objects to destinations and some of the objects and places have privacy issues. The execution of simulations of this logistic problem shows how emotions and trust contribute to improve the performance of agents in terms of both, time savings and privacy protection