Publicaties
2025
Wetenschappelijke publicaties
Zhao, Y., Niu, B., Qin, L., & Wang, S. (2025). An Efficient Task-Oriented Dialogue Policy: Evolutionary Reinforcement Learning Injected by Elite Individuals. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 3429-3442). Association for Computational Linguistics (ACL). https://aclanthology.org/2025.acl-long.171/ [Portal]
Eshuijs, L., Wang, S., & Fokkens, A. (2025). Short-circuiting Shortcuts: Mechanistic Investigation of Shortcuts in Text Classification. In Proceedings of the 29th Conference on Computational Natural Language Learning (pp. 105-125). Association for Computational Linguistics (ACL). https://aclanthology.org/2025.conll-1.8/ [Portal]
Zhu, C., Dastani, M., & Wang, S. (2025). Reducing Variance Caused by Communication in Decentralized Multi-agent Deep Reinforcement Learning. In Y. Vorobeychik, S. Das, & A. Nowe (Eds.), Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025 (pp. 2841-2843). (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). [DOI] [Portal]
2024
Wetenschappelijke publicaties
Han, S., Dastani, M., & Wang, S. (2024). Learning Reward Structure with Subtasks in Reinforcement Learning. In U. Endriss, F. S. Melo, K. Bach, A. Bugarin-Diz, J. M. Alonso-Moral, S. Barro, & F. Heintz (Eds.), ECAI 2024 - 27th European Conference on Artificial Intelligence, Including 13th Conference on Prestigious Applications of Intelligent Systems, PAIS 2024, Proceedings (pp. 2282-2289). (Frontiers in Artificial Intelligence and Applications; Vol. 392). IOS Press. [DOI] [Portal]
Brons, A., Wang, S., Visser, B., Kröse, B., Bakkes, S., & Veltkamp, R. (2024). Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview. Journal of Medical Internet Research, 26, Article e47774. [DOI] [Portal]
Zhao, Y., Dastani, M., & Wang, S. (2024). Bootstrapped Policy Learning: Goal Shaping for Efficient Task-oriented Dialogue Policy Learning. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, 2024(May), 2615-2617. https://dl.acm.org/doi/10.5555/3635637.3663245 [Portal]
Dudzik, B. J. W., van der Waa, J. S., Chen, P. Y., Dobbe, R., de Troya, Í. M. D. R., Bakker, R. M., de Boer, M. H. T., Smit, Q. T. S., Dell’Anna, D., Erdogan, E., Yolum, P., Wang, S., Santamaría, S. B., Krause, L., & Kamphorst, B. A. (2024). Viewpoint: Hybrid Intelligence Supports Application Development for Diabetes Lifestyle Management. Journal of Artificial Intelligence Research, 80, 919-929. [DOI] [Portal]
Chang, W. T., Wang, S., Kramer, S., Oey, M., & Ben Allouch, S. (2024). Human-Centered AI for Dementia Care: Using Reinforcement Learning for Personalized Interventions Support in Eating and Drinking Scenarios. In F. Lorig, J. Tucker, A. D. Lindstrom, F. Dignum, P. Murukannaiah, A. Theodorou, & P. Yolum (Eds.), HHAI 2024: Hybrid Human AI Systems for the Social Good - Proceedings of the 3rd International Conference on Hybrid Human-Artificial Intelligence (pp. 84-93). (Frontiers in Artificial Intelligence and Applications; Vol. 386). IOS Press BV. [DOI] [Portal]
Chen, P. Y., Baez Santamaria, S., De Boer, M. H. T., Den Hengst, F., Kamphorst, B. A., Smit, Q., Wang, S., & Wolff, J. (2024). Intelligent Support Systems for Lifestyle Change: Integrating Dialogue, Information Extraction, and Reasoning. In F. Lorig, J. Tucker, A. D. Lindstrom, F. Dignum, P. Murukannaiah, A. Theodorou, & P. Yolum (Eds.), HHAI 2024: Hybrid Human AI Systems for the Social Good - Proceedings of the 3rd International Conference on Hybrid Human-Artificial Intelligence (pp. 457-459). (Frontiers in Artificial Intelligence and Applications; Vol. 386). IOS Press BV. [DOI] [Portal]
Sarhan, I., Toth, B., Mosteiro, P., & Wang, S. (2024). TaxoCritic: Exploring Credit Assignment in Taxonomy Induction with Multi-Critic Reinforcement Learning. In G. Serasset, H. G. Oliveira, & G. V. Oleskeviciene (Eds.), Proceedings of the Workshop on DLnLD 2024: Deep Learning and Linked Data at LREC-COLING 2024 - Workshop Proceedings (pp. 14-30). (Proceedings of the Workshop on DLnLD 2024: Deep Learning and Linked Data at LREC-COLING 2024 - Workshop Proceedings). European Language Resources Association (ELRA). https://aclanthology.org/2024.dlnld-1.2 [Portal]
Zhu, CX., Dastani, M., & Wang, SH. (2024). Correction: A survey of multi-agent deep reinforcement learning with communication (vol 38, pg 4, 2024). Autonomous Agents and Multi-Agent Systems, 38(1), Article 11. [DOI] [Repository]
Lu, Z., Wang, S., Ren, X.-L., Costas, R., & Metze, T. (2024). Influential Node Detection on Graph on Event Sequence. In H. Cherifi, L. M. Rocha, C. Cherifi, & M. Donduran (Eds.), Complex Networks and Their Applications XII: Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023, Volume 3 (1 ed., pp. 147-158). (Studies in Computational Intelligence; Vol. 1143). Springer. [DOI] [Portal]
Zhao, Y., Yin, K., Wang, Z., Dastani, M., & Wang, S. (2024). Decomposed Deep Q-Network for Coherent Task-Oriented Dialogue Policy Learning. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 32, 1380-1391. [DOI] [Repository]
Hui, Y., Chekol, M., & Wang, S. (2024). Leveraging Graph Embedding for Opinion Leader Detection in Dynamic Social Networks. In T. Kliegr (Ed.), Artificial Intelligence. ECAI 2023 International Workshops: Kraków, Poland, September 30 – October 4, 2023, Proceedings, Part II (1 ed., pp. 5-22). Springer. [DOI]
Zhu, C., Dastani, M., & Wang, S. (2024). A survey of multi-agent deep reinforcement learning with communication. Autonomous Agents and Multi-Agent Systems, 38(1), Article 4. [DOI] [Repository]
2023
Wetenschappelijke publicaties
Zhang, C., Wang, S., Liefooghe, B., Spelt, H., Xu, J., & IJsselsteijn, W. A. (2023). Using AI Methods for Health Behavior Change. CEUR Workshop Proceedings, 3474, 1-5. https://ceur-ws.org/Vol-3474/preface4.pdf [Repository]
Han, S., Dastani, M., & Wang, S. (2023). Model-Based Sparse Communication in Multi-Agent Reinforcement Learning. In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (Vol. 2023-May, pp. 439–447). (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). [DOI] [Repository]
2022
Wetenschappelijke publicaties
Zhang, C., Wang, S., Tjong Kim Sang, E., Adriaanse, M. A., Tummers, L., Schraagen, M., Qi, J., Dastani, M., & Aarts, H. (2022). Spatiotemporal variations of public opinion on social distancing in the Netherlands: Comparison of Twitter and longitudinal survey data. Frontiers in Public Health, 10, 1-14. Article 856825. [DOI] [Repository]
Sporrel, K., Wang, S., Ettema, D. D. F., Nibbeling, N., Krose, B. J. A., Deutekom, M., de Boer, R. D. D., & Simons, M. (2022). Just-in-Time Prompts for Running, Walking, and Performing Strength Exercises in the Built Environment: 4-Week Randomized Feasibility Study. JMIR Formative Research, 6(8), 1-18. Article e35268. [DOI] [Repository]
Zhao, Y., Qin, H., Zhenyu, W., Zhu, C., & Wang, S. (2022). A Versatile Adaptive Curriculum Learning Framework for Task-oriented Dialogue Policy Learning. In Findings of the Association for Computational Linguistics: NAACL 2022 (pp. 711-723). Association for Computational Linguistics. [DOI] [Repository]
2021
Wetenschappelijke publicaties
Zhao, Y., Wang, Z., Zhu, C., & Wang, S. (2021). Efficient Dialogue Complementary Policy Learning via Deep Q-network Policy and Episodic Memory Policy. In M.-F. Moens, X. Huang, L. Specia, & S. W. Yih (Eds.), Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (pp. 4311-4323). Association for Computational Linguistics. [DOI] [Repository]
Wang, S., Zhang, C., Kröse, B., & van Hoof, H. (2021). Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator. Journal of Medical Systems, 45(12), 1-8. Article 102. [DOI] [Repository]
Wang, S., Sporrel, K., van Hoof, H., Simons, M., de Boer, R. D. D., Ettema, D., Nibbeling, N., Deutekom, M., & Kröse, B. (2021). Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study. International Journal of Environmental Research and Public Health, 18(11), 1-15. Article 6059. [DOI] [Repository]
Sporrel, K., De Boer, R. D. D., Wang, S., Nibbeling, N., Simons, M., Deutekom, M., Ettema, D., Castro, P. C., Dourado, V. Z., & Kröse, B. (2021). The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining. Frontiers in Public Health, 8, 1-19. Article 528472. [DOI] [Repository]
Sporrel, K., Nibbeling, N., Wang, S., Ettema, D., & Simons, M. (2021). Unraveling Mobile Health Exercise Interventions for Adults: Scoping Review on the Implementations and Designs of Persuasive Strategies. JMIR mHealth and uHealth, 9(1), 1-19. Article e16282. [DOI] [Repository]
Wang, S., Scheider, S., Sporrel, K., Deutekom, M., Timmer, J., & Kröse, B. J. A. (2021). What are Good Situations for Running? A Machine Learning Study using Mobile and Geographical Data. Frontiers in Public Health, 8, 1-15. Article 536370. [DOI] [Repository]
2020
Wetenschappelijke publicaties
Wang, S., Schraagen, M., Tjong Kim Sang, E., & Dastani, M. (2020). Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media. In K. Verspoor, K. Bretonnel Cohen, M. Conway, B. de Bruijn, M. Dredze, R. Mihalcea, & B. Wallace (Eds.), Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at the 2020 Conference on Empirical Methods in Natural Language Processing Association for Computational Linguistics. [DOI] [Repository]
Jiang, B., Hou, J., Zhou, W., Yang, C., Wang, S., & Pang, L. (2020). METNet: A Mutual Enhanced Transformation Network for Aspect-based Sentiment Analysis. In Proceedings of the 28th International Conference on Computational Linguistics (pp. 162-172). International Committee on Computational Linguistics. [DOI] [Repository]
Jiang, B., Zhou, W., Yang, J., Yang, C., Wang, S., & Pang, L. (2020). PEDNet: A Persona Enhanced Dual Alternating Learning Network for Conversational Response Generation. In D. Scott, N. Bel, & C. Zong (Eds.), Proceedings of the 28th International Conference on Computational Linguistics (pp. 4089-4099). International Committee on Computational Linguistics. [DOI] [Repository]
QI, JI., Bloemen, V., Wang, S., van Wijk, J., & van de Wetering, H. (2020). STBins: Visual Tracking and Comparison of Multiple Data Sequences Using Temporal Binning. IEEE Transactions on Visualization and Computer Graphics, 26(1), 1054-1063. [DOI]
2018
Wetenschappelijke publicaties
Wang, S., Songhori, M. J., Chang, S., & Terano, T. (2018). How triangle structure in inter-firm human network affects bankruptcy evolution: An agent-based simulation study with real and artificial data. In D. N. Cassenti (Ed.), Advances in Human Factors in Simulation and Modeling - Proceedings of the AHFE 2017 International Conference on Human Factors in Simulation and Modeling, 2017 (pp. 285-296). (Advances in Intelligent Systems and Computing; Vol. 591). Springer. [DOI]
Wang, S., Timmer, J. A., Scheider, S., Sporrel, K., Akata, Z., & Kroese, B. (2018). A Data-driven Study on Preferred Situations for Running. In UbiComp 2018 Adjunct Proceedings
2017
Wetenschappelijke publicaties
Wang, S., Moise, I., Helbing, D., & Terano, T. (2017). Early Signals of Trending Rumor Event in Streaming Social Media. In 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) (pp. 654-659). (Proceedings - International Computer Software and Applications Conference; Vol. 2). IEEE. [DOI]
Tan, L., Wang, S., & Terano, T. (2017). Study on the social networks based on Japanese social events from name card data. In Y. Demazeau, J. Gao, G. Xu, J. Kozlak, K. Muller, I. Razzak, H. Chen, & Y. Gu (Eds.), 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC) (pp. 1-5). IEEE. [DOI]
2016
Wetenschappelijke publicaties
Wang, S., Songhori, M. J., Chang, S., & Terano, T. (2016). The impact of human relationship on bankruptcy-related evolution of inter-firm trade network. In T. M. Roeder, P. I. Frazier, R. Szechtman, & E. Zhou (Eds.), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016 (Vol. 0, pp. 3405-3416). Article 7822371 IEEE. [DOI]
2015
Wetenschappelijke publicaties
Wang, S., & Terano, T. (2015). Detecting rumor patterns in streaming social media. In F. Luo, K. Ogan, M. J. Zaki, L. Haas, B. C. Ooi, V. Kumar, S. Rachuri, S. Pyne, H. Ho, X. Hu, S. Yu, M. H.-I. Hsiao, & J. Li (Eds.), Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015 (pp. 2709-2715). Article 7364071 IEEE. [DOI]