Journal articles on the topic 'Combinatorial multi-armed bandits'
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Ontañón, Santiago. "Combinatorial Multi-armed Bandits for Real-Time Strategy Games." Journal of Artificial Intelligence Research 58 (March 29, 2017): 665–702. http://dx.doi.org/10.1613/jair.5398.
Full textXu, Lily, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, and Milind Tambe. "Dual-Mandate Patrols: Multi-Armed Bandits for Green Security." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 17 (May 18, 2021): 14974–82. http://dx.doi.org/10.1609/aaai.v35i17.17757.
Full textZhou, Huozhi, Lingda Wang, Lav Varshney, and Ee-Peng Lim. "A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6933–40. http://dx.doi.org/10.1609/aaai.v34i04.6176.
Full textMoraes, Rubens, Julian Mariño, Levi Lelis, and Mario Nascimento. "Action Abstractions for Combinatorial Multi-Armed Bandit Tree Search." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 14, no. 1 (September 25, 2018): 74–80. http://dx.doi.org/10.1609/aiide.v14i1.13018.
Full textDu, Yihan, Siwei Wang, and Longbo Huang. "A One-Size-Fits-All Solution to Conservative Bandit Problems." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 8 (May 18, 2021): 7254–61. http://dx.doi.org/10.1609/aaai.v35i8.16891.
Full textAgarwal, Mridul, Vaneet Aggarwal, Abhishek Kumar Umrawal, and Chris Quinn. "DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 8 (May 18, 2021): 6557–65. http://dx.doi.org/10.1609/aaai.v35i8.16812.
Full textGai, Yi, Bhaskar Krishnamachari, and Rahul Jain. "Combinatorial Network Optimization With Unknown Variables: Multi-Armed Bandits With Linear Rewards and Individual Observations." IEEE/ACM Transactions on Networking 20, no. 5 (October 2012): 1466–78. http://dx.doi.org/10.1109/tnet.2011.2181864.
Full textOntanon, Santiago. "The Combinatorial Multi-Armed Bandit Problem and Its Application to Real-Time Strategy Games." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 9, no. 1 (June 30, 2021): 58–64. http://dx.doi.org/10.1609/aiide.v9i1.12681.
Full textZhang, Chen, and Steven C. H. Hoi. "Partially Observable Multi-Sensor Sequential Change Detection: A Combinatorial Multi-Armed Bandit Approach." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5733–40. http://dx.doi.org/10.1609/aaai.v33i01.33015733.
Full textNasim, Imtiaz, Ahmed S. Ibrahim, and Seungmo Kim. "Learning-Based Beamforming for Multi-User Vehicular Communications: A Combinatorial Multi-Armed Bandit Approach." IEEE Access 8 (2020): 219891–902. http://dx.doi.org/10.1109/access.2020.3043301.
Full textChen, Xiaowei, Jiawei Xue, Zengxiang Lei, Xinwu Qian, and Satish V. Ukkusuri. "Online eco-routing for electric vehicles using combinatorial multi-armed bandit with estimated covariance." Transportation Research Part D: Transport and Environment 111 (October 2022): 103447. http://dx.doi.org/10.1016/j.trd.2022.103447.
Full textTaheri Javan, Nastooh, Masoud Sabaei, and Vesal Hakami. "IEEE 802.15.4.e TSCH-Based Scheduling for Throughput Optimization: A Combinatorial Multi-Armed Bandit Approach." IEEE Sensors Journal 20, no. 1 (January 1, 2020): 525–37. http://dx.doi.org/10.1109/jsen.2019.2941012.
Full textHan, Kai, Yuntian He, Alex X. Liu, Shaojie Tang, and He Huang. "Differentially Private and Budget-Limited Bandit Learning over Matroids." INFORMS Journal on Computing 32, no. 3 (July 2020): 790–804. http://dx.doi.org/10.1287/ijoc.2019.0903.
Full textBandyopadhyay, Sambaran, Pratyush Kumar, and Vijay Arya. "Planning Curtailment of Renewable Generation in Power Grids." Proceedings of the International Conference on Automated Planning and Scheduling 26 (March 30, 2016): 353–57. http://dx.doi.org/10.1609/icaps.v26i1.13779.
Full textWan Ariffin, Wan Nur Suryani Firuz Wan, Xinruo Zhang, Mohammad Reza Nakhai, Hasliza A. Rahim, and R. Badlishah Ahmad. "Online Learning Approach for Predictive Real-Time Energy Trading in Cloud-RANs." Sensors 21, no. 7 (March 25, 2021): 2308. http://dx.doi.org/10.3390/s21072308.
Full textPerera, R. Malinga, Bastian Oetomo, Benjamin I. P. Rubinstein, and Renata Borovica-Gajic. "HMAB." Proceedings of the VLDB Endowment 16, no. 2 (October 2022): 216–29. http://dx.doi.org/10.14778/3565816.3565824.
Full textShweta, Jain, and Gujar Sujit. "A Multiarmed Bandit Based Incentive Mechanism for a Subset Selection of Customers for Demand Response in Smart Grids." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 02 (April 3, 2020): 2046–53. http://dx.doi.org/10.1609/aaai.v34i02.5577.
Full textLykouris, Thodoris, Karthik Sridharan, and Éva Tardos. "Small-Loss Bounds for Online Learning with Partial Information." Mathematics of Operations Research, January 25, 2022. http://dx.doi.org/10.1287/moor.2021.1204.
Full textWang, Yingfei, Hua Ouyang, Chu Wang, Jianhui Chen, Tsvetan Asamov, and Yi Chang. "Efficient Ordered Combinatorial Semi-Bandits for Whole-Page Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 31, no. 1 (February 13, 2017). http://dx.doi.org/10.1609/aaai.v31i1.10939.
Full textLetard, Alexandre, Tassadit Amghar, Olivier Camp, and Nicolas Gutowski. "COM-MABs: From Users' Feedback to Recommendation." International FLAIRS Conference Proceedings 35 (May 4, 2022). http://dx.doi.org/10.32473/flairs.v35i.130560.
Full textZhou, Yitong, Hesheng Sun, Yibo Jin, Yanfang Zhu, Yuan Li, Zhuzhong Qian, Sheng Zhang, and Sanglu Lu. "Inference replication at edges via combinatorial multi-armed bandit." Journal of Systems Architecture, June 2022, 102636. http://dx.doi.org/10.1016/j.sysarc.2022.102636.
Full textYan, Cairong, Haixia Han, Yanting Zhang, Dandan Zhu, and Yongquan Wan. "Dynamic clustering based contextual combinatorial multi-armed bandit for online recommendation." Knowledge-Based Systems, September 2022, 109927. http://dx.doi.org/10.1016/j.knosys.2022.109927.
Full textWang, Hengzhi, Yongjian Yang, En Wang, Wenbin Liu, Yuanbo Xu, and Jie Wu. "Truthful User Recruitment for Cooperative Crowdsensing Task: A Combinatorial Multi-Armed Bandit Approach." IEEE Transactions on Mobile Computing, 2022, 1. http://dx.doi.org/10.1109/tmc.2022.3153451.
Full textSong, Yunchao, Chen Liu, Wenyi Zhang, Yiliang Liu, Haibo Zhou, and Xuemin Shen. "Two Stage Beamforming in Massive MIMO: A Combinatorial Multi-Armed Bandit Based Approach." IEEE Transactions on Vehicular Technology, 2023, 1–6. http://dx.doi.org/10.1109/tvt.2022.3229312.
Full textModi, Navikkumar, Philippe Mary, and Christophe Moy. "Transfer restless multi-armed bandit policy for energy-efficient heterogeneous cellular network." EURASIP Journal on Advances in Signal Processing 2019, no. 1 (October 21, 2019). http://dx.doi.org/10.1186/s13634-019-0637-1.
Full textShu, Zhaogang, Haoxian Feng, Tarik Taleb, and ZhiFang Zhang. "A Novel Combinatorial Multi-Armed Bandit Game to Identify Online the Changing Top-K Flows in Software-Defined Networks." SSRN Electronic Journal, 2023. http://dx.doi.org/10.2139/ssrn.4326503.
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