作者：
Butola, RajatLi, YimingKola, Sekhar ReddyNational Yang Ming Chiao Tung University
Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation
The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan
In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SP...
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Numerous information visualization techniques are available for utilizing and analyzing big data. Among which, network visualization that employs node-link diagrams can determine the relationship among multidimensiona...
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Mobile systems with lithium-ion batteries have become very popular. Higher performance, longer battery life, and safer operation are required for those systems. We have developed a method of the thermal management sys...
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A multiagent system (MAS) has recently gained public attention as a technique to solve competition and cooperation in distributed systems. However, MAS's vulnerability due to the propagation of failures prevents f...
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A multiagent system (MAS) has recently gained public attention as a technique to solve competition and cooperation in distributed systems. However, MAS's vulnerability due to the propagation of failures prevents from applying to a large scale system. Then, this paper proposes a general composition technique to improve its reliability easily applied to the existent MAS. Proposed system monitors messages between agents to detect undesirable behaviors (failures). Collecting related information, the system generates global information of interdependence between agents and expresses it in a graph. This interdependence graph enables us to detect or predict undesirable behaviors. This paper also shows that the system can optimize performance of MAS and improve adaptively its reliability under complicated and dynamic environment by applying the global information acquired from analysis of the interdependence graph to a replication system.
The coordination of cooperating Unmanned Aerial Vehicles (UAVs) has become an active area of research. The approaches to coordinate these so-called swarms generally include a solution to a class of problems called Are...
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H.264/SVC is a widely used compression standard with a very high lossy compression rate. The completeness of the H.264/SVC bitstream is very crucial in achieving high quality video decompression. This is especially tr...
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The widespread interest toward online learning at higher education worldwide brings about necessity toward an smart Learning Management System (LMS), LMS with analytic functionalities, to increase learning outcome of ...
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This paper presents an approach for speeding up the convergence of adaptive intelligent agents using reinforcement learning algorithms. Speeding up the learning of an intelligent agent is a complex task since the choi...
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ISBN:
(纸本)9789898565105
This paper presents an approach for speeding up the convergence of adaptive intelligent agents using reinforcement learning algorithms. Speeding up the learning of an intelligent agent is a complex task since the choice of inadequate updating techniques may cause delays in the learning process or even induce an unexpected acceleration that causes the agent to converge to a non-satisfactory policy. We have developed a technique for estimating policies which combines instance-based learning and reinforcement learning algorithms in Markovian environments. Experimental results in dynamic environments of different dimensions have shown that the proposed technique is able to speed up the convergence of the agents while achieving optimal action policies, avoiding problems of classical reinforcement learning approaches.
In this paper, we find the correlated mutations of positions among structural proteins of spike, envelop, membrane and nucleocapsid proteins in amino acid sequences of SARS-CoV-2. Here, we adopt the algorithm designed...
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Graphs are among the most frequently used structures in computerscience. Some of the properties that must be checked in many applications are connectivity, acyclicity and the Eulerian and Hamiltonian properties. In t...
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