In this paper, we introduce some new signature schemes and secret sharing schemes from the known Gröbner basis cryptosystems. Then, we discuss the issues related to the security of these schemes. Finally, we draw...
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The main challenge in the area of reinforcement learning is scaling up to larger and more complex problems. Aiming at the scaling problem of reinforcement learning, a scalable reinforcement learning method, DCS-SRL, i...
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The main challenge in the area of reinforcement learning is scaling up to larger and more complex problems. Aiming at the scaling problem of reinforcement learning, a scalable reinforcement learning method, DCS-SRL, is proposed on the basis of divide-and-conquer strategy, and its convergence is proved. In this method, the learning problem in large state space or continuous state space is decomposed into multiple smaller subproblems. Given a specific learning algorithm, each subproblem can be solved independently with limited available resources. In the end, component solutions can be recombined to obtain the desired result. To ad- dress the question of prioritizing subproblems in the scheduler, a weighted priority scheduling algorithm is proposed. This scheduling algorithm ensures that computation is focused on regions of the problem space which are expected to be maximally productive. To expedite the learning process, a new parallel method, called DCS-SPRL, is derived from combining DCS-SRL with a parallel scheduling architecture. In the DCS-SPRL method, the subproblems will be distributed among processors that have the capacity to work in parallel. The experimental results show that learning based on DCS-SPRL has fast convergence speed and good scalability.
Dynamic Bayesian Network (DBN) is a graphical model for representing temporal stochastic processes. Learning the structure of DBN is a fundamental step for parameter learning, inference and application. For large scal...
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In this paper, we investigate belief revision in possibilistic logic, which is a weighted logic proposed to deal with incomplete and uncertain information. Existing revision operators in possibilistic logic are restri...
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We tackle the problem of improving the helpful actions technique for contingent planning. A revision of the heuristic computation that rearranges the relaxed planning graph is proposed, where the unreasonable conforma...
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In this paper, one-dimensional （1D） nonlinear beam equations of the form utt - uxx ＋ uxxxx ＋ mu = f （u） with Dirichlet boundary conditions are considered, where the nonlinearity f is an analytic, odd function an...
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In this paper, one-dimensional （1D） nonlinear beam equations of the form utt - uxx ＋ uxxxx ＋ mu = f （u） with Dirichlet boundary conditions are considered, where the nonlinearity f is an analytic, odd function and f（u） = O（u3）. It is proved that for all m ∈ （0, M＊] R （M＊ is a fixed large number）, but a set of small Lebesgue measure, the above equations admit small-amplitude quasi-periodic solutions corresponding to finite dimensional invariant tori for an associated infinite dimensional dynamical system. The proof is based on an infinite dimensional KAM theory and a partial Birkhoff normal form technique.
Time interrupts play an important role in the system. When time interrupts occur, system will inspect process running state, providing an opportunity to schedule, which is important for improving system real time perf...
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Link prediction in networks has attracted increasing attention by researchers coming from different branches of science, and has been applied in many important domains, such as protein-protein interaction networks in ...
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This paper focuses efforts on the problem of computing the inverse of cardinal direction relations (CRs), which is a fundamental problem in qualitative spatial reasoning. We study the quite expressive cardinal directi...
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This paper focuses efforts on the problem of computing the inverse of cardinal direction relations (CRs), which is a fundamental problem in qualitative spatial reasoning. We study the quite expressive cardinal direction relation model for extended objects, known as cardinal direction calculus (CDC). We first concentrate on a set of a special type of CRs defined in CDC, named rectangle-CRs, and compute the inverse of rectangle-CRs by exploiting the evident connection between basic rectangle- CRs and interval relations. Then, we consider progressively the general cardinal direction relations in CDC, or called CDC relations for short, the inverse of which is computed by reducing to the computation of the inverse of rectangle-CRs. This simplifies the computations. Analyzing in theory and the final results both demonstrate that our algorithms are correct and complete and the time complexity is bounded by a constant number of operations.
According to the attributes of nodes and the linkages between them, most real-world complex networks could be assortative and disassortative. Community structures are ubiquitous in both types of networks. The ability ...
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