Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
In wireless ad hoc networks, autonomous nodes are reluctant to forward others' packets because of the nodes' limited energy. However, such selfishness and noncooperation ...
Previous numerical and analytical work has shown that synaptic coupling can allow a network of model neurons to synchronize despite heterogeneity in intrinsic parameter values. In ...
Wireless mesh networks (WMN) are finding increasing usage in city-wide deployments for providing network connectivity. Mesh routers in WMNs typically use multiple wireless channel...
We consider a system with two service classes with heterogeneous traffic characteristics and Quality-of-Service requirements. The available bandwidth is shared between the two tra...