In order to solve the problem of insufficient information mining and low degree of personalization due to the single data dimension of cognitive diagnosis test question recommendation, this paper proposes a personaliz...
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A mathematical model is proposed to estimate the amount of studied educational material, taking into account the influence of students' cognitive abilities diversity and experience of educational tasks composition...
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Utility mining is a recent mounting field in data mining. It has many research directions like Negative profit, On-shelf utility mining, rare utility itemset mining, utility based Association rule mining, Utility Sequ...
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In this paper, a sliding mode controller (SMC) with PID surface is designed for the trajectory tracking control of a robot manipulator using different optimization algorithms such as, Antlion optimization Algorithm (A...
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In this paper, a sliding mode controller (SMC) with PID surface is designed for the trajectory tracking control of a robot manipulator using different optimization algorithms such as, Antlion optimization Algorithm (ALO) Sine Cosine Algorithm (SCA) Grey Wolf Optimizer (GWO) and Whale Optimizer Algorithm (WOA). The aim of this work is to introduce a novel SMC-PID-ALO to control nonlinear systems, especially the position of two of the joints of a 2DOF robot manipulator. The basic idea is to determinate four optimal parameters (K-p, K-i, K-d and lamda) ensuring the best performance of a robot manipulator system, minimizing the integral time absolute error criterion (ITAE) and the integral time square error criterion (ISTE). The robot manipulator is modeled in Simulink and the control is implemented using the MATLAB environment. The obtained simulation results prove the robustness of ALO in comparison with other algorithms.
Recent advancements in differentiable simulators highlight the potential of policy optimization using simulation gradients. Yet, these approaches are largely contingent on the continuity and smoothness of the simulati...
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Recent advancements in differentiable simulators highlight the potential of policy optimization using simulation gradients. Yet, these approaches are largely contingent on the continuity and smoothness of the simulation, which precludes the use of certain simulation engines, such as Mujoco. To tackle this challenge, we introduce the adaptive analytic gradient. This method views the Q function as a surrogate for future returns, consistent with the Bellman equation. By analyzing the variance of batched gradients, our method can autonomously opt for a more resilient Q function to compute the gradient when encountering rough simulation transitions. We also put forth the Adaptive-Gradient Policy optimization (AGPO) algorithm, which leverages our proposed method for policy learning. On the theoretical side, we demonstrate AGPO's convergence, emphasizing its stable performance under non-smooth dynamics due to low variance. On the empirical side, our results show that AGPO effectively mitigates the challenges posed by non-smoothness in policy learning through differentiable simulation. Copyright 2024 by the author(s)
Nowadays a wide range of complex optimization problems are solved in a distributed way by edge devices. This paper presents a new method of optimization, based on metaheuristics independent runs, objective function ca...
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Strategically allocating capital and safeguarding investors from potential adverse conditions are important challenges in finance. Building upon Markowitz's Modern Portfolio Theory (MPT), which advocates diversify...
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In this paper, a multi-strategy enhanced slime mould algorithm (IMSMA) is proposed to address issues such as population initialization, convergence speed, and the tendency to fall into local optima in the slime mould ...
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In mobile edge computing, the traditional multiple access and computation offload methods based on average performance constraints can no longer meet the demand of delay sensitive services of mobile user devices. Base...
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The new power load management system, as a modern power monitoring system in the context of rapid development of science and technology, can effectively enhance the communication function and detection performance of ...
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