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We consider a modular method to reinforcement learning that represents uncertainty of model parameters by maintaining probability distributions over them. The algorithm we call MBDP (model-based Bayesian dynamic programming) can be decomposed into two parallel types of inference: model learning and policy learning. During learning a model, we update posterior distributions of a model over observations...
We explore the problem of Chinese character description and font designing in this paper, a novel dynamic description method for Chinese character was proposed. This method includes a dynamic description algorithm by using stroke-segments-vector, stroke elements and generation algorithm by using feature points and their weights, characteristic expression and weight vector of the feature points. Our...
Wireless interference does not necessarily result in the lost of all the information of the desired signal. In this paper, we study the signature allocation in wireless networks by exploiting the retained signal feature under interference. The commonly used node signature includes MAC address and PN sequence. However, both of them take a lot of time to identify the signature when the network scale...
A hierarchical reinforcement learning method based on heuristic reward function is proposed to solve the problem of “curse of dimensionality”, that is the states space will grow exponentially in the number of features, and low convergence speed. The method can reduce state spaces greatly and can enhance the speed of the study. Choose actions with favorable purpose and efficiency so as to optimize...
Grid computing is the technology for building Internet-wide computing environment in which distributed and heterogeneous resources are integrated. However, in Grid environment, job scheduling is confronted with a great challenge. This paper focuses on lightweight jobs scheduling in Grid Computing. An Adaptive Fine-grained Job Scheduling (AFJS) algorithm is proposed. Compared with other fine-grained...
Grid resource management and scheduling are confronted with a great challenge. This paper presented a dynamic resource price-adjusting (RPA) strategy in computational Grid. Three new concepts and two new evaluation standards are defined. On the basis of these theories, a Grid resource scheduling algorithm based on marker-driven using dynamic RPA strategy is proposed. With the help of GridSim toolkit,...
Grid resource scheduling is one of the popular issues in grid computing research field. Ant colony algorithm (ACA) is an effective method to solve NP (non-deterministic polynomial) problems. By studying the process of resource scheduling in grid environment and ant colony algorithm for classic TSP problem, a strategy of resource scheduling based on ACA in grid environment was proposed. Then, the new...
BACnet (building automation and control networks) is a standard data communication protocol for building automation and control systems. BACnet adopts Master-Slave/Token-Passing (MS/TP) as one of its local area networking options. The MS/TP protocol is designed specifically for building automation and control systems. In this study, we introduce a new algorithm of implementing bandwidth dynamic allocation...
Based on the differentially perturbed velocity particle swarm optimization, an improved multi-swarm particle swarm optimization (MSPSO) is presented to improve the problem of the slow convergence and diversity loss. The algorithm makes the number of populations search at the same time in the same
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