Abstract: Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex ...
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=5 ...
Abstract: This paper describes a byte-oriented binary transmission code and its implementation. This code is particularly well suited for high-speed local area networks and similar data links, where ...
Two-Stage Cooperation Multiobjective Evolutionary Algorithm Guided by Constraint-Sensitive Variables
Abstract: Constrained multiobjective optimization problems are widespread in practical engineering fields. Scholars have proposed various effective constrained multiobjective evolutionary algorithms ...
Abstract: This paper presents the first discrete-time distributed algorithm to track the tightest ellipsoids that outer approximates the global dynamic intersection of ellipsoids. Given an undirected ...
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=34 ...
Abstract: Next Point-of-interest recommendation involves modeling user interactions with Point-of-interests (PoIs) to analyze user behavior patterns and suggest future scenarios. Data sparsity ...
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=55 ...
Abstract: In the field of multi-intersection signal control, Reinforcement Learning (RL) has demonstrated significant technical benefits in terms of optimization speed, stability, and scalability.
Abstract: Spectrum cartography (SC) aims to construct a global radio-frequency (RF) map across multiple domains, e.g., space, frequency and time, from sparse sensor samples. Recent state-of-the-art SC ...
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