Budhitama Subagdja, D Shanthoshigaa, and Ah-Hwee Tan. 2025. Relation Prediction in Knowledge Graphs: A Self-Organizing Neural Network Approach. Accepted by Neural Networks, https://doi.org/10.1016/j.neunet.2025.107679.
Budhitama Subagdja, D Shanthoshigaa, and Ah-Hwee Tan. 2025. DisambiguART: A Neural-based Inference Model for Knowledge Graph Disambiguation. Accepted by ACM Transactions on Knowledge Discovery from Data, https://dl.acm.org/doi/10.1145/3737880 [PDF]
Minghong Geng, Shubham Pateria, Budhitama Subagdja, Lin Li, Xin Zhao, and Ah-Hwee Tan. 2025. L2M2: A Hierarchical Framework Integrating Large Language Model and Multi-agent Reinforcement Learning. Accepted by the 34th International Joint Conference on Artificial Intelligence (IJCAI 2025).
Minghong Geng. 2025. Hierarchical Frameworks for Scaling-up Multi-agent Coordination. Accepted by the 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025).
Minghong Geng, Shubham Pateria, Budhitama Subagdja, and Ah-Hwee Tan. 2025. MOSMAC: A Multi-agent Reinforcement Learning Benchmark on Sequential Multi-Objective Tasks. Accepted by the 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025). [PDF]
Shubham Pateria, Budhitama Subagdja, and Ah-Hwee Tan. FedART: A Neural Model Integrating Federated Learning and Adaptive Resonance Theory, Neural Networks, Volume 181, 2025, 106845, ISSN 0893-6080, https://doi.org/10.1016/j.neunet.2024.106845. [PDF].
Francisco Munguia Galeano, Ah-Hwee Tan and Ze Ji. Deep Reinforcement Learning with Explicit Context Representation, in IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 1, pp. 419-432, Jan. 2025, doi: 10.1109/TNNLS.2023.3325633. [PDF]
Minghong Geng, Shubham Pateria, Budhitama Subagdja and Ah-Hwee Tan. HiSOMA: A Hierarchical Multi-Agent Model Integrating Self-Organizing Neural Networks with Multi-Agent Deep Reinforcement Learning. Expert Systems with Applications, Volume 252, Part A, 2024, 124117, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2024.124117. [PDF]
Budhitama Subagdja, D Shanthoshigaa, Zhaoxia Wang and Ah-Hwee Tan. Machine Learning for Refining Knowledge Graphs: A Survey. ACM Computing Surveys, Volume 56, Issue 6, Article No.: 156, Pages 1 - 38, https://doi.org/10.1145/3640313. [PDF]
Budhitama Subagdja, Sanchari Dan, and Ah-Hwee Tan. Self-Supervised Fine-tuning for Neural Expert Finding, 23rd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2024), Bangkok, Thailand, 9-12 December 2024, Pages 38-45, https://doi.org/10.1109/WI-IAT62293.2024.00014. [PDF]
Ah-Hwee Tan, Weng-Yan Ying, Budhitama Subagdja, Anni Huang, D Shanthoshigaa, Tony Chin-Ian Tay and Iris Rawtaer. Predicting Mild Cognitive Impairment through Ambient Sensing and Artificial Intelligence. Proceedings of 2nd IEEE Conference on Artificial Intelligence (CAI 2024), Singapore, Singapore, 2024, Pages 1098-1104, https://doi.org/10.1109/CAI59869.2024.00198. [PDF]
Doudou Wu, Shubham Pateria, Budhitama Subagdja and Ah-Hwee Tan. FedSTEM-ADL: A Federated Spatial-Temporal Episodic Memory Model for ADL Prediction. Proceedings of 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, 2024, Pages 1 - 8, https://doi.org/10.1109/IJCNN60899.2024.10650422. [PDF]
Tony Chin Ian Tay, Ah-Hwee Tan, Rathi Mahendran, Tze Pin Ng, and Iris Rawtaer. In-Home Sensors for Monitoring Cognitive Decline: A Community-Based Study Protocol Paper. Alzheimer’s Association International Conference Neuroscience Next, April 22-25, 2024. (Poster)
Minghong Geng. Scaling up Cooperative Multi-Agent Reinforcement Learning Systems. In Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024), Pages 2737–2739. Richland, SC. International Foundation for Autonomous Agents and Multiagent Systems, 2024, https://dl.acm.org/doi/10.5555/3635637.3663271. [PDF] [Poster]
Minghong Geng, Shubham Pateria, Budhitama Subagdja and Ah-Hwee Tan. Benchmarking MARL on Long Horizon Sequential Multi-Objective Tasks, in Proceedings of 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024), Pages 2279–2281, https://dl.acm.org/doi/10.5555/3635637.3663133. [PDF] [Poster]
Khaing Phyo Wai, Minghong Geng, Shubham Pateria, Budhitama Subagdja and Ah-Hwee Tan. Explaining Sequences of Actions in Multi-agent Deep Reinforcement Learning Models, in Proceedings of 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024), Pages 2537–2539, https://dl.acm.org/doi/10.5555/3635637.3663219. [PDF] [Poster]
Zhaoxia Wang, Zhenda Hu, Seng-Beng Ho, Erik Cambria, and Ah-Hwee Tan. MiMuSA—mimicking human language understanding for fine-grained multi-class sentiment analysis. Neural Computing and Applications (2023): 1-15. https://link.springer.com/article/10.1007/s00521-023-08576-z.
Jingfeng Cui, Zhaoxia Wang, Seng-Beng Ho, and Erik Cambria. Survey on sentiment analysis: evolution of research methods and topics. Artificial Intelligence Review (2023): 1-42. https://link.springer.com/article/10.1007/s10462-022-10386-z.
Zhaoxia Wang, Zhenda Hu, Fang Li, Seng-Beng Ho, and Erik Cambria. Learning-based stock trending prediction by incorporating technical indicators and social media sentiment. Cognitive Computation (2023): 1-11. https://link.springer.com/article/10.1007/s12559-023-10125-8.
Xinjing Song, Di Wang, Chai Quek, Ah-Hwee Tan and Yanjiang Wang. Spatial-Temporal Episodic Memory Modeling for ADLs: Encoding, Retrieval, and Prediction. Complex & Intelligent Systems. (2023). https://doi.org/10.1007/s40747-023-01298-8
Ah-Hwee Tan, Dipti Srinivasan and Chunyan Miao, Conference Report on 2022 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2022), in IEEE Computational Intelligence Magazine, vol. 18, no. 3, pp. 6-9, Aug. 2023, doi: 10.1109/MCI.2023.3278554.
Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan and Chai Quek. Value-based Subgoal Discovery and Path Planning for Reaching Long-Horizon Goals, in IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2023.3240004.
Tianze Luo, Zichen Chen, Budhitama Subagdja and Ah-Hwee Tan. Real-time Hierarchical Map Segmentation for Coordinating Multi-Robot Exploration. in IEEE Access, vol. 11, pp. 15680-15692, 2023, doi: 10.1109/ACCESS.2022.3171925. [PDF]
Khaing Phyo Wai, Minghong Geng, Budhitama Subagdja, Shubham Pateria and Ah-Hwee Tan. Towards Explaining Sequences of Actions in Multi-Agent Deep Reinforcement Learning Model. In Proceedings of the 22nd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023), 2023-May, pp. 2325–2327. https://dl.acm.org/doi/abs/10.5555/3545946.3598922. [PDF] [Poster]
Zhenda Hu, Zhaoxia Wang, Yinglin Wang and Ah-Hwee Tan, MSRL-Net: A Multi-level Semantic Relation-enhanced Learning Network for Aspect-Based Sentiment Analysis. Accepted by Expert Systems with Applications.
Zhenda Hu, Zhaoxia Wang, Yinglin Wang and Ah-Hwee Tan. Aspect Sentiment Triplet Extraction Incorporating Syntactic Constituency Parsing Tree and Commonsense Knowledge Graph. Cognitive Computation (2022). https://doi.org/10.1007/s12559-022-10078-4. [PDF & Code]
Wai-Cheong Lincoln Lew, Di Wang, Kai Keng Ang, Joo-Hwee Lim, Chai Quek and Ah-Hwee Tan. EEG-Video Emotion-based Summarization: Learning with EEG Auxiliary Signals. IEEE Transactions on Affective Computing, Vol. 13, No. 4 (Oct-Dec. 2022), 1827-1839, doi: 10.1109/TAFFC.2022.3208259. [PDF]
Yue Hu, Budhitama Subagdja, Ah-Hwee Tan and Quanjun Yin. Vision-based Topological Mapping and Navigation with Self-Organizing Neural Networks. IEEE Transactions on Neural Networks and Learning Systems, Vol. 33, no. 12, (December 2022) 7101-7113, doi: 10.1109/TNNLS.2021.3084212. [PDF]
Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan and Chai Quek. End-to-End Hierarchical Reinforcement Learning with Integrated Subgoal Discovery. IEEE Transactions of Neural Networks and Learning Systems, Vol. 33, No. 12 (December 2022) 7778–7790, doi: 10.1109/TNNLS.2021.3087733. [PDF]
Seng-Khoon Teh, Iris Rawtaer and Ah-Hwee Tan. Predictive Self-Organizing Neural Networks for In-Home Detection of Mild Cognitive Impairment. Expert Systems With Applications., Vol. 205, 2022, https://doi.org/10.1016/j.eswa.2022.117538. [PDF]
Yue Hu, Budhitama Subagdja, Ah-Hwee Tan, Chai Quek and Quanjun Yin. Spatio-Temporal Episodic Memory for Identifying Asymptomatic COVID-19 Cases. Neural Computation and Applications, 2022; 34(17): 14859–14879. Published online 2022 May 14. doi: 10.1007/s00521-022-07210-8. [PDF]
Weigui Jair Zhou, Budhitama Subagdja, Ah-Hwee Tan and Darren Wee-Sze Ong. Hierarchical Control of Multi-Agent Reinforcement Learning Team in Real-Time Strategy (RTS) Games. Expert Systems with Applications, Vol. 186 (December 2021) 115707, https://doi.org/10.1016/j.eswa.2021.115707. [PDF]
Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan and Chai Quek. Hierarchical Reinforcement Learning: A Comprehensive Survey. ACM Computing Survey, vol. 54, no. 5 (June 2021), Article No. 109, 1–35. https://doi.org/10.1145/3453160. [PDF]
Shan Gao, Ah-Hwee Tan and Rossi Setchi. Learning ADL Daily Routines with Spatiotemporal Neural Networks. IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 1 (January 2021) 143-153. doi: 10.1109/TKDE.2019.2924623. [PDF]
Yue Hu, Kai Xu, Budhitama Subagdja, Ah-Hwee Tan and Quanjun Yin. Interpretable Goal Recognition for Path Planning with ART Networks. In proceedings, 14th International Joint Conference on Neural Networks (IJCNN 2021), Shenzhen, China, 2021.
Haibo Pen, Quan Wang, and Zhaoxia Wang. Boundary precedence image inpainting method based on Self-organizing Maps. Knowledge-Based Systems 216 (2021): 106722. [PDF]
Renjie Wan, Boxin Shi, Haoliang Li, Ling-Yu Duan, Ah-Hwee Tan and Alex C. Kot. CoRRN: Cooperative Reflection Removal Network. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 42, no. 12 (December 2020), 2969-2982, doi: 10.1109/TPAMI.2019.2921574. [PDF]
Yizhang Wang, Di Wang, Wei Pang, Chunyan Miao, Ah-Hwee Tan and You Zhou. A systematic density-based clustering method using anchor points. Neurocomputing, 400 (2020) 352-370, https://doi.org/10.1016/j.neucom.2020.02.119. [PDF]
Yizhang Wang, Di Wang, Xiaofeng Zhang, Wei Pang, Chunyan Miao, Ah-Hwee Tan and You Zhou. McDPC: multi-center density peak clustering. Neural Computing and Applications, 2020, https://doi.org/10.1007/s00521-020-04754-5. [PDF]
Budhitama Subagdja, Hanyi Tay and Ah-Hwee Tan. Who Am I?: Towards Social Self-Awareness for Intelligent Agents. In proceedings, International Joint Conference on Artificial Intelligence (IJCAI 2020), Special track on AI for Computational Sustainability and Human well-being. [PDF]
Wai Cheong Lincoln Lew, Di Wang, Katsiaryna Shylouskaya, Zhuo Zhang, Kai Keng Ang, Joo-Hwee Lim and Ah-Hwee Tan. EEG-based Emotion Recognition Using Spatial-Temporal Representation via Bi-GRU. In proceedings, 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2020).
Shubham Pateria, Budhitama Subagdja and Ah-Hwee Tan. Hierarchical Reinforcement Learning with Integrated Count-based Discovery of Salient Subgoals. In proceedings, 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020).
Zhaoxia Wang, Seng-Beng Ho, and Erik Cambria. Multi-level fine-scaled sentiment sensing with ambivalence handling. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28.04 (2020): 683-697. [PDF].
Zhaoxia Wang, Haibo Pen, Ting Yang, and Quan Wang. Structure-priority image restoration through genetic algorithm optimization. IEEE Access 8 (2020): 90698-90708. [PDF] [PDF & MATLAB Code] [Transferring MATLAB Code to Python]
Zhaoxia Wang, and Zhiping Lin. Optimal feature selection for learning-based algorithms for sentiment classification. Cognitive Computation 12.1 (2020): 238-248. [PDF]
Zhaoxia Wang, Seng-Beng Ho, and Erik Cambria. A review of emotion sensing: categorization models and algorithms. Multimedia Tools and Applications 79.47 (2020): 35553-35582. [PDF]
Ah-Hwee Tan, Budhitama Subagdja, Di Wang and Lei Meng. Self-organizing Neural Networks for Universal Learning and Multimodal Memory Encoding. Neural Networks, 120 (2019) 58-73. [PDF]
Lei Meng, Ah-Hwee Tan and Chunyan Miao. Salience-aware adaptive resonance theory for large-scale sparse data clustering. Neural Networks, 120 (2019) 143-157. [PDF]
You-Lu Xing, Xiao-Feng Shi, Fu-Rao Shen, Jin-Xi Zhao, Jing-Xin Pan and Ah-Hwee Tan. Perception Coordination Network: A Neuro Framework for Multi-Modal Concept Acquisition and Binding. IEEE Transactions on Neural Networks and Learning Systems, Vol. 30, No. 4 (2019) 1104-1118. [PDF]
Budhitama Subagdja and Ah-Hwee Tan. A Coordination Framework for Multi-Agent Persuasion and Adviser Systems. Expert Systems with Applications, Vol. 116 (2019) 31-51. [PDF]
Milan Parmar, Di Wang, Xiaofeng Zhang, Ah-Hwee Tan, Chunyan Miao, Jianhua Jiang, and You Zhou. REDPC: A residual error-based density peak clustering algorithm. Neurocomputing, Vol. 348 (2019) 82-96. [PDF]
Shubham Pateria, Budhitama Subagdja and Ah-Hwee Tan. Multi-agent Reinforcement Learning in Spatial Domain Tasks using Inter Subtask Empowerment Rewards. In proceedings, SSCI 2019: 86-93, Xiamen, China, December 2019.
Tianze Luo, Budhitama Subagdja, Di Wang and Ah-Hwee Tan. Multi-Agent Collaborative Exploration through Graph-based Deep Reinforcement Learning. In proceedings, 2019 IEEE International Conference on Agents (ICA), Jinan, China, October 2019. (Best Paper Award)
Zichen Chen, Budhitama Subagdja and Ah-Hwee Tan. End-to-end Deep Reinforcement Learning for Multi-agent Collaborative Exploration. In proceedings, 2019 IEEE International Conference on Agents (ICA), Jinan, China, October 2019.
Budhitama Subagdja and AhHwee Tan. Beyond Autonomy: The Self and Life of Social Agents. In proceedings, 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), Montreal, Canada, May 2019.
Di Wang, Ah-Hwee Tan and Chunyan Miao. Modelling Autobiographical Memory Loss Across Life Span. In proceedings, Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 19), Honolulu, Hawaii, USA, January 2019.
Seng-Beng Ho, and Zhaoxia Wang, On true language understanding , International Conference on Artificial Intelligence and Security, 87-99. [PDF]
Seng-Beng Ho, and Zhaoxia Wang. Language and Robotics: Complex Sentence Understanding. International Conference on Intelligent Robotics and Applications. Springer, Cham, 2019. [PDF]