As genomic and proteomic data is collected from highthroughput methods on a daily basis, subcellular components are identified and their in vitro behavior is characterized. Howev...
Salim Khan, William Gillis, Carl Schmidt, Keith De...
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
Abstract. Learning in a multiagent environment is complicated by the fact that as other agents learn, the environment effectively changes. Moreover, other agents’ actions are oft...
In spatial graphs with a vast number of nodes, it is difficult to compute a solution to graph optimisation problems. We propose an approach using meta-level agents for multi-agents...
This paper proposes a new multiagent planning approach to coordination synthesis that views distributed agents as discrete-event processes. The connection between discreteevent co...