In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
Multi-Agent Systems are a promising way of dealing with large complex problems. However, it is not yet clear just how much complexity or pre-existing structure individual agents m...
Agents are intended to interact in open systems where the knowledge about others (reputation) is incomplete and uncertain. Also, this knowledge about other agents is subjective si...
Through adjustable autonomy (AA), an agent can dynamically vary the degree to which it acts autonomously, allowing it to exploit human abilities to improve its performance, but wi...
This paper presents a system called AgentSalon, which facilitates face-to-face knowledge exchange and discussion by people having shared interests, in museums, schools, offices, a...