By using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rules for unseen situations. These benefits would be ...
This paper presents a community of communicating embodied agents which learn an adjacency-based grammar from user interactions. The agents act as intelligent fridge magnets, each ...
Multiagent learning can be seen as applying ML techniques to the core issues of multiagent systems, like communication, coordination, and competition. In this paper, we address the...
In multi-agent communities, trust is required when agents hold different beliefs or conflicting goals. We present a framework for decomposing agent reputation into competence—...
Abstract. This paper presents a case study for using a relatively recently developed methodology, Behavior Oriented Design, to develop an Intelligent Virtual Agent (IVA). Our usabi...