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...
Multiagent reinforcement learning problems are especially difficult because of their dynamism and the size of joint state space. In this paper a new benchmark problem is proposed, ...
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...