Effects of noise level and surround suppression threshold on model convergence time in the RDK task, experiment III. by Elnaz Nemati (21402730)

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Computation time as a function of the sample size on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Computation time as a function of the sample size on the random graph dataset. by Tomokaze Shiratori (9635271)

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Computation time as a function of the number of variables on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Computation time as a function of the number of variables on the random graph dataset. by Tomokaze Shiratori (9635271)

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Coding schematic. by Dongyan Wang (195482)

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Classical Predictive Coding for motion processing. by Elnaz Nemati (21402730)

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The method for determining the chemical constituents of unknown materials in the algorithm. by Dong Hyeok Choi (12562048)

Completion times for different algorithms. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

Parameters of stimuli used in the study. by Elnaz Nemati (21402730)

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Graphs of the regularization terms. by Tomokaze Shiratori (9635271)

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Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase... by Zhao Li (300229)

Scatter diagram of different principal elements. by Jizhong Wang (7441697)

Main code. by Jingguo Bi (21439766)

Flowchart of PRGA algorithm. by Yicheng Liu (2179626)

“…A case study of a bidirectional disruption during the 08:00–10:00 on the section of Xi’an Metro Line 2 demonstrates that: (1) The proposed model exhibits stronger robustness under demand uncertainty, achieving a reduction of 3 dispatched vehicles and a cost saving of 9,439 RMB by moderately increasing passenger costs by 850 RMB and extending bridging time; (2) The RPGA algorithm outperforms Non-dominated Sorting Genetic Algorithm II (NSGA-II), Reinforcement Learning-based NSGA-II (RLNSGA-II), and Multi-objective Particle Swarm Optimization Algorithm (MOPSO) in hypervolume (HV), generational distance (GD), and non-dominated ratio (NDR); (3) Increasing the rated passenger capacity within a certain range can reduce average passenger delays but correspondingly raises transportation costs. …”

Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30. by Hend Bayoumi (22693738)

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Running time of four algorithms. by Jirong Zeng (20308604)

An example shows how XAI algorithm helps an expert to make a decision. by Shuvo Biswas (21728782)