Most formulations of Reinforcement Learning depend on a single reinforcement reward value to guide the search for the optimal policy solution. If observation of this reward is rar...
In this paper, we discuss and compare several policies to place replicas in tree networks, subject to server capacity and Quality of Service (QoS) constraints. The client requests ...
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
—Ensuring spontaneous ad hoc interoperation in decentralized ubiquitous computing environments is challenging, because of heterogeneous resources and divergent policies. Centrali...
Venkatraman Ramakrishna, Peter L. Reiher, Leonard ...
Chip-Multi-Processors (CMP) utilize multiple energy-efficient Processing Elements (PEs) to deliver high performance while maintaining an efficient ratio of performance to energy-c...