An Enhanced Deep Reinforcement Learning-Based Global Router for VLSI Design

Enhanced Experience Replay for Deep Reinforcement Learning

Operation Scheduling of MGs Based on Deep Reinforcement Learning Algorithm

: In this paper, the operation scheduling of Microgrids (MGs), including Distributed Energy Resources (DERs) and Energy Storage Systems (ESSs), is proposed using a Deep Reinforcement Learning (DRL) based approach. Due to the dynamic characteristic of the problem, it firstly is formulated as a Markov Decision Process (MDP). Next, Deep Deterministic Policy Gradient (DDPG) algorithm is presented t...

Deep Learning Design for Technology Enhanced Learning

To address the salient challenge of designing Technology Enhanced Learning (TEL) amidst wide-ranging and profound technological changes, within the Web 2.0 landscape and beyond, we are developing the notion of Deep Learning Design (DLD). This is a paradigm that we hold is important to both better understanding and realising learning in the digital age that counters the sort of technological det...

Vision-based Deep Reinforcement Learning

Recently, Google Deepmind showcased how Deep learning can be used in conjunction with existing Reinforcement Learning (RL) techniques to play Atari games[11], beat a world-class player [14] in the game of Go and solve complicated riddles [3]. Deep learning has been shown to be successful in extracting useful, nonlinear features from high-dimensional media such as images, text, video and audio [...

VLSI Based Robust Router Architecture

In this paper, we introduce networking solution by using VLSI architecture techniques to router design for networking system to provide control over the network. We attempts to overcome latency and time reduction issue and can provide multipurpose networking router by means of verilog and it was synthesized in Xilinx 13.2 version, simulated Modelsim 10.0 version. The approach enables the router...