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 ...
In this paper, we describe a computer-supported cooperative learning system in education and the results of its deployment. The system, called I-MINDS, consists of a set of teache...
The field of multiagent decision making is extending its tools from classical game theory by embracing reinforcement learning, statistical analysis, and opponent modeling. For ex...
Michael Wunder, Michael Kaisers, John Robert Yaros...
Hardware agents as a part of cooperative multi-agent systems act in dynamically changing environments and accomplish tasks jointly. Since the pure hybrid plan representation provid...
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah