Biologically-inspired cognitive architecture is used to organize and direct information processing in neural network models. Specifically, the interaction between working memory, episodic memory, and semantic memory, inspired by psychological and biological discoveries, enables learning and integrated information processing in embodied intelligent agents. In our cognitive architecture inspired efforts, we have codified and computationalized these processes and applied them to various single and multi-agent intelligent systems. Self-awareness in intelligent agents is also an important aspect of cognitively-inspired adaptive systems, which forms part of our research focus.
Enhancing neural networks with knowledge models that capture human-like symbolic and commonsense knowledge, as well as enhancing natural language understanding with human-like fine-grained multi-level sentiment and emotion processing and analysis, we aim to go beyond the current paradigm of natural language processing and endow intelligent systems with the deep capability of human-like language understanding. Applying to the tasks of question-answering and conversational agents based on the understanding of text supported by commonsense knowledge, this naturally provides explainability at the fundamental level to the processes involved.
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[2025/05] Congratulations to Budhi and Shantho for their paper on Relation Prediction in Knowledge Graphs: A Self-Organizing Neural Network Approach accepted by Neural Networks journal.
[2025/05] Congratulations to Budhi and Shantho for their paper on DisambiguART: A Neural-based Inference Model for Knowledge Graph Disambiguation accepted by ACM TKDD journal.
[2025/04] Congratulations to Minghong for his paper on L2M2: A Hierarchical Framework Integrating Large Language Model and Multi-agent Reinforcement Learning accepted for presentation at 34th International Joint Conference on Artificial Intelligence (IJCAI 2025), Montreal, Canada, Aug 16 - Aug 22, 2025 and Guangzhou, China, Aug 28 - Aug 31, 2025.
[2025/02] Congratulations to Minghong for his paper on Hierarchical Frameworks for Scaling-up Multi-agent Coordination accepted for presentation at 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025), Detroit, USA, May 19 - May 23, 2025.
[2024/12] Congratulations to Minghong for his paper on MOSMAC: A Multi-agent Reinforcement Learning Benchmark on Sequential Multi-Objective Tasks accepted for presentation at 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025), Detroit, USA, May 19 – May 23, 2025.
[2024/10] Congratulations to Shubham for his paper on FedART: A Neural Model Integrating Federated Learning and Adaptive Resonance Theory accepted by Neural Networks Journal.
[2024/10] Congratulations to Budhi for his paper on Self-Supervised Fine-tuning for Neural Expert Finding accepted by 2024 IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2024).
[2024/04] Congratulations to Minghong for his paper on HiSOMA: A Hierarchical Multi-Agent Model Integrating Self-Organizing Neural Networks with Multi-Agent Deep Reinforcement Learning accepted by Expert Systems with Applications Journal.
[2024/03] Congratulations to Doudou for her paper on FedSTEM-ADL: A Federated Spatial-Temporal Episodic Memory Model for ADL Prediction accepted for presentation at IEEE World Congress on Computational Intelligence (IEEE WCCI 2024), Yokohama, Japan, 30 June - 5 July 2024.
[2024/03] Congratulations to the SINEW team for the paper on Predicting Mild Cognitive Impairment through Ambient Sensing and Artificial Intelligence accepted for presentation at 2nd IEEE International Conference on Artificial Intelligence (CAI 2024), Singapore, 25-27 June 2024.
[2024/01] Congratulations to Minghong for his paper on Scaling up Cooperative Multi-agent Reinforcement Learning Systems accepted by AAMAS 2024 Doctoral Consortium.
[2023/12] Congratulations to Budhi for his paper on Machine Learning for Refining Knowledge Graphs: A Survey, accepted for publication in ACM Computing Surveys.
[2023/12] Congratulations to Minghong for his paper on Benchmarking MARL on Long Horizon Sequential Multi-Objective Tasks accepted by AAMAS 2024.
[2023/12] Congratulations to Khaing for her paper on Explaining Sequences of Actions in Multi-agent Deep Reinforcement Learning Model accepted by AAMAS 2024.
(2023/04/30): Congratulations to Zhaoxia for her paper on Learning-based stock trending prediction by incorporating technical indicators and social media sentiment has been accepted by Cognitive Computation.
(2023/04/30): Congratulations to Jingfeng for his paper on Survey on sentiment analysis: evolution of research methods and topics has been accepted by Artificial Intelligence Review.
(2023/04/30): Congratulations to Zhaoxia for her paper on MiMuSA—mimicking human language understanding for fine-grained multi-class sentiment analysis has been accepted by Neural Computing and Applications.
(2023/01/17): Congratulations to Shubham for his paper on Value-based Subgoal Discovery and Path Planning for Reaching Long-Horizon Goals accepted by IEEE Transactions on Neural Networks and Learning Systems.
(2023/01/04): Congratulations to Khaing for her paper on Towards Explaining Sequences of Actions in Multi-Agent Deep Reinforcement Learning Model accepted by The 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023).
(2022/12/30): Congratulations to Zhenda for his paper on MSRL-Net: A Multi-level Semantic Relation-enhanced Learning Network for Aspect-Based Sentiment Analysis accepted by Expert Systems with Applications.
(2022/12/28): Congratulations to Zhenda for his paper on Aspect Sentiment Triplet Ex-traction Incorporating Syntactic Constituency Parsing Tree and Commonsense Knowledge Graph published by Cognitive Computation. [PDF & Code]
(2022/9/30): Congratulations to Budhi for winning the inaugural SMU Research Staff Excellence Award 2022!
(2022/9/11): Congratulations to Lincoln for his paper on EEG-Video Emotion-based Summarization: Learning with EEG Auxiliary Signals accepted by IEEE Transactions on Affective Computing.
Congratulations to Seng Khoon for his paper on Predictive Self-Organizing Neural Networks for In-Home Detection of Mild Cognitive Impairment accepted by Expert Systems With Applications.
Congratulations to Tianze for his paper on Real-time Hierarchical Map Segmentation for Coordinating Multi-Robot Exploration accepted by IEEE Access.
Congratulations to Hu Yue for his paper on Spatio-Temporal Episodic Memory for Identifying Asymptomatic COVID-19 Cases accepted by Neural Computation and Applications.
2022 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2022) will be held in Singapore on December 4-7, 2022.
Budhi's paper on Hierarchical Control of Multi-Agent Reinforcement Learning Team in Real-Time Strategy (RTS) Games has been published online by Expert Systems With Applications. [PDF]
Zhenda's paper on Stock Market Trend Forecasting Based on Multiple Textual Features: A Deep Learning Method has been accepted by the 33rd IEEE International Conference on Tools with Artificial Intelligence, https://ictai.computer.org/
Ah-Hwee Tan has been conferred the inaugural Jubilee Technology Fellowship for his work on AI and Cognitive Computing (2021-2024)
Hu Yue's paper on Vision-based Topological Mapping and Navigation with Self-Organizing Neural Networks has been accepted by IEEE Transactions on Neural Networks and Learning Systems. [PDF]
Shubham Pateria's paper on End-to-End Hierarchical Reinforcement Learning with Integrated Subgoal Discovery has been accepted by IEEE Transactions of Neural Networks and Learning Systems. [PDF]
Shubham Pateria's paper on Hierarchical Reinforcement Learning: A Comprehensive Survey has been published by ACM Computing Survey, vol. 54, no. 5 (June 2021), Article No.: 109, 1–35. https://doi.org/10.1145/3453160. [PDF]
Gao Shan's paper on Learning ADL Daily Routines with Spatiotemporal Neural Networks has been published by IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 1, pp. 143-153, 1 Jan. 2021, doi: 10.1109/TKDE.2019.2924623. [PDF]