In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

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We describe the adaptive source routing (ASR) method which is a first attempt to combine adaptive routing and source routing methods. In ASR, the adaptivity of each packet is determined at the source processor. Every packet can be routed in a fully adaptive or partially adaptive or non–adaptive manner, all within the same network at the same time. We evaluate and compare performance of the prop...

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

This study presents a robust and rigorous method based on intelligent models, namely radial basis function networks optimized by particle swarm optimization (PSO-RBF), multilayer perceptron neural networks (MLP-NNs), and adaptive neuro-fuzzy inference system optimized by particle swarm optimization methods (PSO-ANFIS), for predicting the equilibrium and kinetics of the adsorption of sulfur and ...

Link adaptive relaying (LAR) is one of the most popular techniques which employs soft power scaling approaches at the relay nodes. On the other. Buffer-aided relaying is a new paradigm for wireless cooperative networks. Buffer-Aided Relaying With Adaptive Link Selection – Fixed and Mixed Rate. A wireless relay is a codecadaptive RF receiver with single channel relay. It helps easily deployment ...