Collective activity and autonomous characters: trust-based decision-making system

When working in teams, people make mistakes. To train someone in a collaborative virtual environment to adapt to teammates that bahave non optimally, we propose (1) an augmentation of the ACTIVITY-Description Language as well as mechanisms of propagation of constraints that will facilitate agents' reasoning; and (2) an agent model in which each agent is described through three dimensions (integrity, benevolence, abilities) corresponding to the MDS trust model. Besides each agent has different personal and collective goals and has beliefs about others' integrity, benevolence and abilities. This agent model is associated to a decision-making system that allows agents to adopt human-like behaviors. In particular, agents take others into account and are able to reason on their beliefs about others both when choosing which goal (collective or individual) to focus on and when selecting a task We conducted a preliminary evaluation in which participants evaluated the behaviors produced with our system. © 2017 Lavoisier.