We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Application of autonomous intelligent systems into airspace domain is very important nowadays. The paper presents decentralized collision avoidance algorithm utilizing a solution ...
Teamwork requires that team members coordinate their actions. The representation of the coordination is a key requirement since it influences the complexity and flexibility of r...
— Multi-agent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, etc. Learning approaches to multi-ag...
In multiagent systems, a cooperative action requires a mutual agreement among multiple agents and the agreement is generally reached by exchanging messages between them, but the d...