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Bayesian reinforcement learning provides an elegant solution to the optimal tradeoff between exploration and exploitation of the uncertainty in learning. Unfortunately, the size of the learning parameters grows exponentially with the problem horizon. In this paper, we propose a novel Monte Carlo tree search for Bayesian reinforcement learning approach using a compact factored representation, to solve...
Monte-Carlo tree search (MCTS) combines the generality of stochastic simulation and the accuracy of tree search, which has attracted the great attention of scholars. However, the MCTS search requires a sufficient number of iterations to converge to a good solution, which is more difficult to optimize. In order to solve this problem, this paper presents a point-based incremental pruning (PIP) for Monte-Carlo...
With the popularity of social networking services (SNSs) and the increase of users, individuals' social roles in a social network have become more and more important in terms of the recommendation of personalized services and the collective decision-making process. Usually, in an SNS system, active users may not represent the major opinions among the whole users, and most of the users' opinions may...
We proposed a novel model to predict human's visual attention when free-viewing webpages. Compared with natural images, webpages are usually full of salient regions such as logos, text, and faces, while few of them attract human's attention in a short sight. Moreover, webpages perform distinct viewing patterns which are quite different from the natural images. In this paper, we introduced multi-features...
The high development of emerging computing paradigms, such as Ubiquitous Computing, Mobile Computing, and Social Computing, has brought us a big change from all walks of our work, life, learning and entertainment. Especially, with the high accessibility of social networking services along with the increasingly pervasive use of portable wireless mobile computing devices, more and more populations have...
Dynamic videos are viewed fundamentally different from static images. Besides spatial features, motion feature also plays an important role as a temporal factor. Most existing video saliency models usually employ optical flow to represent the motion feature. However, optical flow often suffers from the discontinuity problem. And we also notice that human fixations in one single video frame are much...
Formal methods in robotic motion planning have emerged as a hot research topic recently due to its correct-by-design nature, and most results haven been based on nonprobabilistic discrete models. To better handle the environment uncertainties, sensor noise and actuator imperfection, control problems in probabilistic systems like Markov Chain (MC) and Markov Decision Process (MDP) have also been studied...
In this paper, a novel method is proposed to perform saliency detection in news video. This method comprises bottom-up attention model which considers low level features to produce bottom-up saliency map and top-down attention model which utilizes high level factors to generate top-down saliency map. In bottom-up attention model, color image is represented as quaternion. Then the quaternion discrete...
We present a mesh less method for local deformation and crack simulation of plastic thin shell. Although previous mesh less methods have done the similar simulations, there exists a problem that the moment matrix may be singular. And the result is that the shape function cannot be constructed to finish the simulation. Special work is needed to deal with the problem. In this paper, we propose a mesh...
Applications based on Deterministic Finite Automata (DFA) are important for many tasks, including lexing in web browsers, routing in networks, decoding in cryptography and so on. The efficiency of these applications are often critical, but parallelizing them is difficult due to strong dependences among states. Recent years have seen some employment of speculative execution to address that problem...
Classical finite-difference time-domain (FDTD) method has been widely used in computational electromagnetics, but for electrically large domains and for late-time analysis, FDTD method begins to show its limitations due to the accumulation of phase errors. To solve this problem, several methods have been proposed such as high-order schemes and four-stage Runge-Kutta integrator. Recently, the symplectic...
In a mobile computing system, mobile hosts may move around cells, resulting in a considerable cost for locating and retrieving the recovery information, which is necessary for fault tolerance. To speed up the recovery, traditionally, recovery information is migrated according to the location of the mobile host. In this paper, a scheme for efficiently handling the recovery information is proposed....
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