Embedded systems consisting of collaborating agents capable of interacting with their environment are becoming ubiquitous. It is crucial for these systems to be able to adapt to t...
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...
The efficient simulation of multi-agent systems presents particular challenges which are not addressed by current parallel discrete event simulation (PDES) models and techniques. ...
Michael Lees, Brian Logan, Rob Minson, Ton Oguara,...
We develop a novel mechanism for coordinated, distributed multiagent planning. We consider problems stated as a collection of single-agent planning problems coupled by common soft...
Agents in a multi-agent system do not act in a vacuum. The outcome of their efforts depends on the environment in which they seek to act, and in particular on the efforts of other...
H. Van Dyke Parunak, Robert Bisson, Sven A. Brueck...