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Publication search results
found 800 matches
- 2024
- Chiwen Qu, Xiaoning Peng, Qilan Zeng:
Learning search algorithm: framework and comprehensive performance for solving optimization problems. Artif. Intell. Rev. 57(6): 139 (2024) - Yen-Fen Lee, Pei-Ying Chen, Shu-Chen Cheng:
Improve learning retention, self-efficacy, learning attitude and problem-solving skills through e-books based on sequential multi-level prompting strategies. Educ. Inf. Technol. 29(3): 3663-3680 (2024) - Sayed Pedram Haeri Boroujeni, Elnaz Pashaei:
A hybrid chimp optimization algorithm and generalized normal distribution algorithm with opposition-based learning strategy for solving data clustering problems. Iran J. Comput. Sci. 7(1): 65-101 (2024) - Hong Guo, Jin Yang, Jun Yang:
Machine learning and evolutionary optimization approach for solving the flexible job-shop scheduling problem. J. Intell. Fuzzy Syst. 46(4): 8845-8863 (2024) - Funing Li, Sebastian Lang, Bingyuan Hong, Tobias Reggelin:
A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups. J. Intell. Manuf. 35(3): 1107-1140 (2024) - Quanfeng Li, Zhihua Guo, Fei Chao, Xiang Chang, Longzhi Yang, Chih-Min Lin, Changjing Shang, Qiang Shen:
Solving Robotic Trajectory Sequential Writing Problem via Learning Character's Structural and Sequential Information. IEEE Trans. Cybern. 54(2): 1096-1108 (2024) - Sirui Chen, Zhaowei Zhang, Yaodong Yang, Yali Du:
STAS: Spatial-Temporal Return Decomposition for Solving Sparse Rewards Problems in Multi-agent Reinforcement Learning. AAAI 2024: 17337-17345 - Haoran Ye, Jiarui Wang, Helan Liang, Zhiguang Cao, Yong Li, Fanzhang Li:
GLOP: Learning Global Partition and Local Construction for Solving Large-Scale Routing Problems in Real-Time. AAAI 2024: 20284-20292 - Beniamino Di Martino, Domenico Di Sivo, Antonio Esposito:
Architectural Patterns for Software Design Problem-Solving in the Implementation of Federated Learning Structures Within the E-Health Sector. AINA (5) 2024: 347-356 - Yaoxin Wu, Mingfeng Fan, Zhiguang Cao, Ruobin Gao, Yaqing Hou, Guillaume Sartoretti:
Collaborative Deep Reinforcement Learning for Solving Multi-Objective Vehicle Routing Problems. AAMAS 2024: 1956-1965 - Hao Yin, Fan Chen, Hongjie He:
Solving Offline 3D Bin Packing Problem with Large-sized Bin via Two-stage Deep Reinforcement Learning. AAMAS 2024: 2576-2578 - Dang Viet Anh Nguyen, Aldy Gunawan, Mustafa Misir, Pieter Vansteenwegen:
Q-Learning Based Framework for Solving the Stochastic E-waste Collection Problem. EvoStar 2024: 49-64 - Abdulrahman Nahhas, Andrey Kharitonov, Christian Haertel, Klaus Turowski:
Imitation Learning Based on Deep Reinforcement Learning for Solving Scheduling Problems. HICSS 2024: 1649-1658 - Sang-Yun Lee, Seok-Ju Kang:
A Study on Solving the Data Imbalance Problem for Detecting Heunginjimun Roof Tilt Using Transfer Learning Algorithms. ICAIIC 2024: 221-225 - Caitlin Snyder, Nicole M. Hutchins, Clayton Cohn, Joyce Horn Fonteles, Gautam Biswas:
Analyzing Students Collaborative Problem-Solving Behaviors in Synergistic STEM+C Learning. LAK 2024: 540-550 - Megan Taylor, Abhinava Barthakur, Arslan Azad, Srecko Joksimovic, Xuwei Zhang, George Siemens:
Quantifying Collaborative Complex Problem Solving in Classrooms using Learning Analytics. LAK 2024: 551-562 - Hui-Ju Hung, Wang-Chien Lee, Chih-Ya Shen, Fang He, Zhen Lei:
Leveraging Transfer Learning for Enhancing Graph Optimization Problem Solving. PAKDD (2) 2024: 339-351 - Giang Bui, Nicholas Susanto, Naaz Sibia, Angela M. Zavaleta Bernuy, Michael Liut, Andrew Petersen:
Do Hints Enhance Learning in Programming Exercises? Exploring Students' Problem-Solving and Interactions. SIGCSE (2) 2024: 1578-1579 - Fiona Knoll, John T. Daly, Jess J. Meyer:
Solving Boltzmann Optimization Problems with Deep Learning. CoRR abs/2401.17408 (2024) - Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal, Martin Takác:
Reinforcement Learning for Solving Stochastic Vehicle Routing Problem with Time Windows. CoRR abs/2402.09765 (2024) - Liqiu Dong, Marta A. Zagorowska, Tong Liu, Alex Durkin, Mehmet Mercangöz:
PI-CoF: A Bilevel Optimization Framework for Solving Active Learning Problems using Physics-Information. CoRR abs/2402.13588 (2024) - Cong Zhang, Zhiguang Cao, Yaoxin Wu, Wen Song, Jing Sun:
Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem. CoRR abs/2402.17606 (2024) - Jinyang Jiang, Xiaotian Liu, Tao Ren, Qinghao Wang, Yi Zheng, Yufu Du, Yijie Peng, Cheng Zhang:
Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode. CoRR abs/2403.00318 (2024) - Imanol Echeverria, Maialen Murua, Roberto Santana:
Leveraging Constraint Programming in a Deep Learning Approach for Dynamically Solving the Flexible Job-Shop Scheduling Problem. CoRR abs/2403.09249 (2024) - Zheng Fang, Fucai Ke, Jaeyoung Han, Zhijie Feng, Toby Cai:
Graph Enhanced Reinforcement Learning for Effective Group Formation in Collaborative Problem Solving. CoRR abs/2403.10006 (2024) - Xiuqin Zhong, Shengyuan Yan, Gongqi Lin, Hongguang Fu, Liang Xu, Siwen Jiang, Lei Huang, Wei Fang:
Incorporating Graph Attention Mechanism into Geometric Problem Solving Based on Deep Reinforcement Learning. CoRR abs/2403.14690 (2024) - Frederico Metelo, Stevo Rackovic, Pedro Ákos, Cláudia Soares:
PeersimGym: An Environment for Solving the Task Offloading Problem with Reinforcement Learning. CoRR abs/2403.17637 (2024) - Abhijeet Pendyala, Asma Atamna, Tobias Glasmachers:
Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering. CoRR abs/2404.02577 (2024) - Gülsüm Yigit, Mehmet Fatih Amasyali:
Data Augmentation with In-Context Learning and Comparative Evaluation in Math Word Problem Solving. CoRR abs/2404.03938 (2024) - 2023
- Chen Dang:
Apprentissage d'heuristiques pour la résolution de problèmes d'optimisation combinatoire dans les réseaux. (Heuristics Learning for Solving Network Optimization Problems). PSL University, Paris, France, 2023
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