This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis function...
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Due to cost, time, and flexibility constraints, simulators are often used to explore the design space when developing a new processor architecture, as well as when evaluating the ...
—This paper presents a theoretical estimation for idle channel time in a multi-hop environment. Idle channel time is the time proportion of a node during which the channel state ...
Abstract—We tackle the problem of providing minimum datarate guarantees for different classes-of-service in an OFDMAbased network, while obtaining a high system throughput. Our a...