Many applications in multiagent learning are essentially convex optimization problems in which agents have only limited communication and partial information about the function be...
Renato L. G. Cavalcante, Alex Rogers, Nicholas R. ...
We propose Path Disruption Games (PDGs), which consider collaboration between agents attempting stop an adversary from travelling from a source node to a target node in a graph. P...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
Studies of interactions between protein domains and ligands are important in many aspects such as cellular signaling and regulation. In this work, we applied a three-stage knowledg...
Haiyun Lu, Shamima Banu Bte Sm Rashid, Hao Li, Wee...
Fault tolerance will be a fundamental imperative in the next decade as machines containing hundreds of thousands of cores will be installed at various locations. In this context, ...
Esteban Meneses, Celso L. Mendes, Laxmikant V. Kal...