With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
So-called Whittle networks have recently been shown to give tight approximations for the performance of non-locally balanced networks with blocking, including practical routing pol...
Most models of decision-making in neuroscience assume an infinite horizon, which yields an optimal solution that integrates evidence up to a fixed decision threshold; however, u...
The problem of opportunistic access of parallel channels occupied by primary users is considered. Under a continuous-time Markov chain modeling of the channel occupancy by the prim...
Qing Zhao, Stefan Geirhofer, Lang Tong, Brian M. S...
In this paper, a dynamic subcarrier and power allocation problem is considered in the context of asymptotic utility maximization in multi-carrier systems. Using the gradient-based...