This paper introduces an ant-based colony system for the representation of a verbal route description. It is grounded on a natural metaphor that mimics the behavior of ant colonie...
This paper proposes a subjective map representation that enables a robot in a multiagent system to make decisions in a dynamic, hostile environment. A typical situation can be fou...
We present an experimental comparison of different genetic operators regarding their use in an evolutionary learning method that searches for unwanted emergent behavior in a multi...
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...
This work focuses on an emerging extension to traditional agent models, called Hierarchical Mobile Agents model, where an agent can contain other agents recursively. The model ena...