@article{hu2020evolutionary,
title={The Evolutionary Dynamics of Independent Learning Agents in Population Games},
author={Hu, Shuyue and Leung, Chin-Wing and Leung, Ho-fung and Soh, Harold},
journal={arXiv preprint arXiv:2006.16068},
year={2020}}
★ CLeAR Group Members
Shuyue Hu ★, Chin-Wing Leung, Ho-fung Leung, and Harold Soh ★
@article{hu2020evolutionary,
title={The Evolutionary Dynamics of Independent Learning Agents in Population Games},
author={Hu, Shuyue and Leung, Chin-Wing and Leung, Ho-fung and Soh, Harold},
journal={arXiv preprint arXiv:2006.16068},
year={2020}}
Shuyue Hu★, Chin-Wing Leung, Ho-fung Leung, and Harold Soh★
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2022 (Accepted)
@inproceedings{hu2022,
author = {Shuyue Hu and Chin-Wing Leung and Ho-fung Leung and Harold Soh},
title = {The Dynamics of Q-learning in Population Games: a Physics-Inspired Continuity Equation Model},
year = {2022},
booktitle = {International Conference on Autonomous Agents and Multiagent Systems (AAMAS)}}
Abdul Fatir Ansari★, Konstantinos Benidis, Richard Kurle, Ali Caner Turkmen, Harold Soh★, Alex Smola, Bernie Wang, Tim Januschowski
Neural Information Processing Systems (NeurIPS), 2021
@inproceedings{ansari2021deep,
author = {Abdul Fatir Ansari and Konstantinos Benidis and Richard Kurle and Ali Caner Turkmen and Harold Soh and Alex Smola and Bernie Wang and Tim Januschowski},
title = {Deep Explicit Duration Switching Models for Time Series},
year = {2021},
booktitle = {Neural Information Processing Systems (NeurIPS)}}
Tasbolat Taunyazov★, Luar Shui Song★, Eugene Lim★, Hian Hian See, David Lee, Benjamin C.K. Tee, Harold Soh★
IEEE International Conference on Intelligent Robots and Systems (IROS), 2021
@inproceedings{taunyazov2021extended,
title={Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects},
author={Tasbolat Taunyazov and Luar Shui Song and Eugene Lim and Hian Hian See and David Lee and Benjamin C. K. Tee and Harold Soh},
year={2021},
booktitle={IEEE International Conference on Intelligent Robots and Systems (IROS)}}
Kaiqi Chen★, Yong Lee★, and Harold Soh★
IEEE International Conference on Robotics and Automation (ICRA), 2021
@inproceedings{Chen2021MuMMI,
title={Multi-Modal Mutual Information (MuMMI) Training for Robust Self-Supervised Deep Reinforcement Learning},
author={Kaiqi Chen and Yong Lee and Harold Soh},
year={2021},
booktitle={IEEE International Conference on Robotics and Automation (ICRA)}}
Yaqi Xie ★, Fan Zhou ★, and Harold Soh ★
IEEE International Conference on Robotics and Automation (ICRA), 2021
@inproceedings{xie20templogic,
title={Embedding Symbolic Temporal Knowledge into Deep Sequential Models},
author={Yaqi Xie and Fan Zhou and Harold Soh},
year={2021},
booktitle={IEEE International Conference on Robotics and Automation (ICRA)}}
Abdul Fatir Ansari ★, Ming Liang Ang ★, and Harold Soh ★
International Conference on Learning Representations (ICLR), 2021
(28.6% Acceptance Rate)
@inproceedings{fatir2021refining,
title={Refining Deep Generative Models via Discriminator Gradient Flow},
author={Ansari, Abdul Fatir and Ang, Ming Liang and Soh, Harold},
booktitle={International Conference on Learning Representations (ICLR)},
year={2021}}
Nicholas Teh ★, Shuyue Hu ★, and Harold Soh ★
Late Breaking Report, ACM/IEEE Conference on Human Robot Interaction (HRI), 2021
@inproceedings{Teh21,
author = {Teh, Nicholas and Hu, Shuyue and Soh, Harold},
title = {A Theoretical Framework for Large-Scale Human-Robot Interaction with Groups of Learning Agents},
year = {2021},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
booktitle = {Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction},
series = {HRI ’21}}
Sreejith Balakrishnan ★, Quoc Phong Nguyen, Bryan Kian Hsiang Low, and Harold Soh ★
Neural Information Processing Systems (NeurIPS), 2020
(20.1% Acceptance Rate)
@misc{balakrishnan20,
title={Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization},
author={Sreejith Balakrishnan and Quoc Phong Nguyen and Bryan Kian Hsiang Low and Harold Soh},
year={2020},
booktitle={Advances in Neural Information Processing Systems}}
Bing Cai Kok★, and Harold Soh ★
Current Robotics Reports, 2020
@article{kok20trust,
title={Trust in Robots: Challenges and Opportunities},
author={Bing Cai Kok and and Harold Soh},
journal={Current Robotics Reports},
year={2020},
doi={10.1007/s43154-020-00029-y}}
Kai Chi Yam, Yochanan Bigman, Pok Man Tang, Remus Ilies, David De Cremer, Harold Soh ★, and Kurt Gray
Journal of Applied Psychology, 2020
Joshua Lee★, Jeffrey Fong★, Bing Cai Kok★, and Harold Soh ★
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
@inproceedings{lee2020trust,
title={Getting to Know One Another: Calibrating Intent, Capabilities and Trust for Human-Robot Collaboration},
author={Joshua Lee and Jeffrey Fong and Bing Cai Kok and and Harold Soh},
booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2020},
month = {October}}
Fuqiang Gu★, Weicong Sng★, Tasbolat Taunyazov★, and Harold Soh ★
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
@inproceedings{gu2020tactile,
title={TactileSGNet: A Spiking Graph Neural Network for Event-based Tactile Object Recognition},
author={Fuqiang Gu and Weicong Sng and Tasbolat Taunyazov and Harold Soh},
booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2020},
month = {October}}
Tasbolat Taunyazov★, Yansong Chua, Ruihan Gao, Harold Soh ★, and Yan Wu
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
@inproceedings{taunyazov2020texture,
title={Fast Texture Classification Using Tactile Neural Coding and Spiking Neural Network},
author={Tasbolat Taunyazov and Yansong Chua and Ruihan Gao and Harold Soh and Yan Wu},
booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2020},
month = {October}}
Tasbolat Taunyazov★, Weicong Sng★, Hian Hian See, Brian Lim, Jethro Kuan★, Abdul Fatir Ansari★, Benjamin Tee, and Harold Soh ★
Robotics: Science and Systems Conference (RSS), 2020
@inproceedings{taunyazov20event,
title={Event-Driven Visual-Tactile Sensing and Learning for Robots},
author={Tasbolat Taunyazoz and Weicong Sng and Hian Hian See and Brian Lim and Jethro Kuan and
Abdul Fatir Ansari and Benjamin Tee and Harold Soh},
year={2020},
booktitle = {Proceedings of Robotics: Science and Systems},
year = {2020},
month = {July}}
Abdul Fatir Ansari★, Jonathan Scarlett, and Harold Soh★
The Conference on Computer Vision and Pattern Recognition (CVPR), 2020
(22.1% Acceptance Rate, Oral Presentation ~5%)
@misc{ansari2019characteristic,
title={A Characteristic Function Approach to Deep Implicit Generative Modeling},
author={Abdul Fatir Ansari and Jonathan Scarlett and Harold Soh},
year={2019},
eprint={1909.07425},
archivePrefix={arXiv}}
Zhi-Xuan Tan, Harold Soh ★, Desmond Ong
Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020
(20.6% Acceptance rate, Oral Presentation)
@inproceedings{tan2020mdmm,
title={Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series},
author={Tan, Zhi-Xuan and Soh, Harold and Ong, Desmond},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={34}}
Harold Soh ★, Yaqi Xie★, Min Chen, and David Hsu
International Journal of Robotics Research (IJRR), 2020
(Impact Factor: 6.134)
@article{soh2019multi,
title={Multi-task trust transfer for human--robot interaction},
author={Soh, Harold and Xie, Yaqi and Chen, Min and Hsu, David},
journal={The International Journal of Robotics Research},
volume = {39},
number = {2-3},
pages = {233-249},
year = {2020},
doi = {10.1177/0278364919866905},
publisher={SAGE Publications Sage UK: London, England}}
Min Chen, Stefanos Nikolaidis, Harold Soh ★, David Hsu, and Siddhartha Srinivasa
ACM Transactions on Human Robot Interaction (THRI), 2020
@article{10.1145/3359616, author = {Chen, Min and Nikolaidis, Stefanos and Soh, Harold and Hsu, David and Srinivasa,
Siddhartha},
title = {Trust-Aware Decision Making for Human-Robot Collaboration: Model Learning and Planning},
year = {2020},
issue_date = {February 2020},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {9},
number = {2},
url = {https://doi.org/10.1145/3359616},
doi = {10.1145/3359616},
journal = {J. Hum.-Robot Interact.},
month = jan,
articleno = {Article 9},
numpages = {23}}
Indu Prasad Bodala★, Bing Cai Kok★, Weicong Sng★, and Harold Soh ★
Late Breaking Report, ACM/IEEE Conference on Human Robot Interaction (HRI), 2020
@inproceedings{bodala2020modeling,
title={Modeling the Interplay of Trust and Attention in HRI: An Autonomous Vehicle Study},
author={Bodala, Indu P and Kok, Bing Cai and Sng, Weicong and Soh, Harold},
booktitle={Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction},
pages={145--147},
year={2020}}
Eugene Lim★, Bing Cai Kok★, Joshua Lee★, Songli Wang★, and Harold Soh ★
Late Breaking Report, ACM/IEEE Conference on Human Robot Interaction (HRI), 2020
@inproceedings{10.1145/3371382.3378308,
author = {Lim, Eugene and Kok, Bing Cai and Wang, Songli and Lee, Joshua and Soh, Harold},
title = {Juiced and Ready to Predict Private Information in Deep Cooperative Reinforcement Learning},
year = {2020},
isbn = {9781450370578},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3371382.3378308},
doi = {10.1145/3371382.3378308},
booktitle = {Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction},
pages = {343–345},
numpages = {3},
keywords = {deep reinforcement learning, cooperative multi-agent system, human-robot collaboration},
location = {Cambridge, United Kingdom},
series = {HRI ’20}}
Yaqi Xie★, Ziwei Xu, Mohan Kankanhalli, Kuldeep S. Meel, and Harold Soh ★
Neural Information Processing Systems (NeurIPS), 2019
(21% Acceptance rate)
@inproceedings{yaqi2019embedding,
title={Embedding Symbolic Knowledge into Deep Networks},
author={Yaqi, Xie and Xu, Ziwei and Meel, Kuldeep S and Kankanhalli, Mohan and Soh, Harold},
booktitle={Advances in Neural Information Processing Systems},
pages={4235--4245},
year={2019}}
Abdul Fatir Ansari★ and Harold Soh ★
Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), 2019
(16.2% Acceptance Rate)
@inproceedings{ansari2019hyperprior,
title={Hyperprior induced unsupervised disentanglement of latent representations},
author={Ansari, Abdul Fatir and Soh, Harold},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={33},
pages={3175--3182},
year={2019}}
Xie Yaqi★, Indu Prasad★, Desmond Ong, David Hsu and Harold Soh ★
ACM/IEEE Conference on Human Robot Interaction (HRI), 2019
(24% Acceptance Rate)
@inproceedings{xie2019robot,
title={Robot Capability and Intention in Trust-Based Decisions Across Tasks},
author={Xie, Yaqi and Bodala, Indu P and Ong, Desmond C and Hsu, David and Soh, Harold},
booktitle={2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)},
pages={39--47},
year={2019},
organization={IEEE}}
Tasbolat Taunyazov★, Hui Fang Koh, Yan Wu, Caixia Cai and Harold Soh ★
IEEE International Conference on Robotics and Automation (ICRA), 2019
@inproceedings{taunyazov2019towards,
title={Towards effective tactile identification of textures using a hybrid touch approach},
author={Taunyazov, Tasbolat and Koh, Hui Fang and Wu, Yan and Cai, Caixia and Soh, Harold},
booktitle={2019 International Conference on Robotics and Automation (ICRA)},
pages={4269--4275},
year={2019},
organization={IEEE}}
Desmond Ong, Harold Soh ★, Jamil Zaki and Noah Goodman
IEEE Transactions on Affective Computing, 2019
(Impact Factor: 6.288)
@article{ong2019applying,
title={Applying Probabilistic Programming to Affective Computing},
author={Ong, Desmond and Soh, Harold and Zaki, Jamil and Goodman, Noah},
journal={IEEE Transactions on Affective Computing},
year={2019},
publisher={IEEE}}
Ga Wu, Kai Luo, Scott Sanner and Harold Soh ★
ACM Recommender Systems Conference (RecSys), 2019
(19% Acceptance Rate)
@inproceedings{wu2019deep,
title={Deep language-based critiquing for recommender systems},
author={Wu, Ga and Luo, Kai and Sanner, Scott and Soh, Harold},
booktitle={Proceedings of the 13th ACM Conference on Recommender Systems},
pages={137--145},
year={2019},
organization={ACM}}
Harold Soh ★, Shu Pan★, Min Chen and David Hsu
IJCAI Best Paper Sister Track, 2019
@inproceedings{ijcai2019-868,
title = {Trust Dynamics and Transfer across Human-Robot Interaction Tasks: Bayesian and Neural Computational Models},
author = {Soh, Harold and Pan, Shu and Chen, Min and Hsu, David},
booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, {IJCAI-19}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
pages = {6226--6230},
year = {2019},
month = {7},
doi = {10.24963/ijcai.2019/868},
url = {https://doi.org/10.24963/ijcai.2019/868},}
Harold Soh ★, Shu Pan★, Min Chen, and David Hsu
Robotics Science and Systems (RSS), 2018
(Best Paper Award Finalist)
@INPROCEEDINGS{Soh-RSS-18,
AUTHOR = {Harold Soh AND Shu Pan AND Chen Min AND David Hsu},
TITLE = {The Transfer of Human Trust in Robot Capabilities across Tasks},
BOOKTITLE = {Proceedings of Robotics: Science and Systems},
YEAR = {2018},
ADDRESS = {Pittsburgh, Pennsylvania},
MONTH = {June},
DOI = {10.15607/RSS.2018.XIV.033}}
Vo Vinh Thanh★ and Harold Soh ★
ACM Recommender Systems Conference (RecSys), 2018
(17.7% Acceptance Rate, Best Long Paper Award Runner-up)
@inproceedings{vo2018generation,
title={Generation meets recommendation: proposing novel items for groups of users},
author={Vo, Thanh Vinh and Soh, Harold},
booktitle={Proceedings of the 12th ACM Conference on Recommender Systems},
pages={145--153},
year={2018},
organization={ACM}}
Min Chen, Stefanos Nikolaidis, Harold Soh ★, David Hsu, and Siddhartha Srinivasa
ACM/IEEE Conference on Human Robot Interaction (HRI), 2018
(23% Acceptance Rate, Best Paper Award Finalist)
@inproceedings{chen2018planning,
title={Planning with trust for human-robot collaboration},
author={Chen, Min and Nikolaidis, Stefanos and Soh, Harold and Hsu, David and Srinivasa, Siddhartha},
booktitle={Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction},
pages={307--315},
year={2018},
organization={ACM}}
Pan Shu★, Min Chen, Stefanos Nikolaidis, David Hsu, and Harold Soh ★
Late Breaking Report, ACM/IEEE Conference on Human Robot Interaction (HRI), 2018
@inproceedings{Shu2018trust,
author = {Shu, Pan and Min, Chen and Bodala, Indu and Nikolaidis, Stefanos and Hsu, David and Soh, Harold},
title = {Human Trust in Robot Capabilities Across Tasks},
booktitle = {Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction},
series = {HRI '18},
year = {2018},
isbn = {978-1-4503-5615-2},
location = {Chicago, IL, USA},
pages = {241--242},
numpages = {2},
url = {http://doi.acm.org/10.1145/3173386.3177034},
doi = {10.1145/3173386.3177034},
acmid = {3177034},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {human robot interaction, trust},}
Young Lee★, Vo Vinh Thanh★, Kar Wai Lim, and Harold Soh ★
Intl. Joint Conference on Artificial Intelligence (IJCAI), 2018
(20.5% Acceptance Rate)
@inproceedings{lee2018z,
title={Z-Transforms and its Inference on Partially Observable Point Processes.},
author={Lee, Young and Vo, Thanh Vinh and Lim, Kar Wai and Soh, Harold},
booktitle={IJCAI},
pages={2369--2375},
year={2018}}
Dusan Sovilj, Scott Sanner, Harold Soh ★, and Hanze Li
ACM User Modeling and Personalization Conference (UMAP), 2018
(28% Acceptance Rate)
@inproceedings{sovilj2018collaborative,
title={Collaborative filtering with behavioral models},
author={Sovilj, Dusan and Sanner, Scott and Soh, Harold and Li, Hanze},
booktitle={Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization},
pages={91--99},
year={2018},
organization={ACM}}
Sean W. Kortschot, Dusan Sovilj, Greg A. Jamieson, Scott Sanner, Chelsea Carrasco, and Harold Soh★
Human Factors: The Journal of the Human Factors and Ergonomics Society
@article{kortschot2018measuring,
title={Measuring and mitigating the costs of attentional switches in active network monitoring for cybersecurity},
author={Kortschot, Sean W and Sovilj, Dusan and Jamieson, Greg A and Sanner, Scott and Carrasco, Chelsea and Soh, Harold},
journal={Human factors},
volume={60},
number={7},
pages={962--977},
year={2018},
publisher={SAGE Publications Sage CA: Los Angeles, CA}}
Harold Soh, Scott Sanner, Madeleine White, and Greg Jamieson
ACM Intelligent User Interfaces (IUI), 2017
(27% Acceptance Rate)
@inproceedings{soh2017deep,
title={Deep sequential recommendation for personalized adaptive user interfaces},
author={Soh, Harold and Sanner, Scott and White, Madeleine and Jamieson, Greg},
booktitle={Proceedings of the 22nd international conference on intelligent user interfaces},
pages={589--593},
year={2017},
organization={ACM}}
Harold Soh and Yiannis Demiris
Journal of Human-Robot Interaction, vol 4, No 3, 2015.
Selected for Presentation at ACM/IEEE HRI 2017
@article{soh2015learning,
title={Learning assistance by demonstration: Smart mobility with shared control and paired haptic controllers},
author={Soh, Harold and Demiris, Yiannis},
journal={Journal of Human-Robot Interaction},
volume={4},
number={3},
pages={76--100},
year={2015},
publisher={Journal of Human-Robot Interaction Steering Committee}}
Harold Soh and Yiannis Demiris
IEEE Transactions on Neural Networks and Learning Systems, 2014.
@article{DBLP:journals/tnn/SohD15,
author = {Harold Soh and Yiannis Demiris},
title = {Spatio-Temporal Learning With the Online Finite and Infinite Echo-State Gaussian Processes},
journal = {{IEEE} Trans. Neural Networks Learn. Syst.},
volume = {26},
number = {3},
pages = {522--536},
year = {2015},
url = {https://doi.org/10.1109/TNNLS.2014.2316291},
doi = {10.1109/TNNLS.2014.2316291},
timestamp = {Mon, 09 Mar 2020 15:52:04 +0100},
biburl = {https://dblp.org/rec/journals/tnn/SohD15.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}}
Harold Soh and Yiannis Demiris
IEEE Transactions on Haptics, 2014.
@article{article,
author = {Soh, Harold and Demiris, Yiannis},
year = {2014},
month = {05},
pages = {512-525},
title = {Incrementally Learning Objects by Touch: Online Discriminative and Generative Models for Tactile-Based Recognition},
volume = {7},
journal = {IEEE Transactions on Haptics},
doi = {10.1109/TOH.2014.2326159}}
Harold Soh and Yiannis Demiris
IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan, 2013.
@INPROCEEDINGS{6696815,
author={Soh, Harold and Demiris, Yiannis},
booktitle={2013 IEEE/RSJ International Conference on Intelligent Robots and Systems},
title={When and how to help: An iterative probabilistic model for learning assistance by demonstration},
year={2013},
volume={},
number={},
pages={3230-3236},
doi={10.1109/IROS.2013.6696815}}
Harold Soh, Yanyu Su and Yiannis Demiris
IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Portugal, 2012.
@INPROCEEDINGS{soh2012tactile,
author={Soh, Harold and Su, Yanyu and Demiris, Yiannis},
booktitle={2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
title={Online spatio-temporal Gaussian process experts with application to tactile classification},
year={2012},
volume={},
number={},
pages={4489-4496},
doi={10.1109/IROS.2012.6385992}}
Harold Soh and Yiannis Demiris
IEEE International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, 2012.
@INPROCEEDINGS{6252504,
author={Soh, Harold and Demiris, Yiannis},
booktitle={The 2012 International Joint Conference on Neural Networks (IJCNN)},
title={Iterative temporal learning and prediction with the sparse online echo state gaussian process},
year={2012},
volume={},
number={},
pages={1-8},
doi={10.1109/IJCNN.2012.6252504}}
Harold Soh and Yiannis Demiris
GECCO’11: Proceedings of the 2011 conference on Genetic and Evolutionary Computation, 713-720, 2011
@inproceedings{10.1145/2001576.2001674,
author = {Soh, Harold and Demiris, Yiannis},
title = {Evolving Policies for Multi-Reward Partially Observable Markov Decision Processes (MR-POMDPs)},
year = {2011},
isbn = {9781450305570},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2001576.2001674},
doi = {10.1145/2001576.2001674},
abstract = {Plans and decisions in many real-world scenarios are made under uncertainty and to satisfy multiple, possibly
conflicting, objectives. In this work, we contribute the multi-reward partially-observable Markov decision process
(MR-POMDP) as a general modelling framework. To solve MR-POMDPs, we present two hybrid (memetic) multi-objective
evolutionary algorithms that generate non-dominated sets of policies (in the form of stochastic finite state controllers).
Performance comparisons between the methods on multi-objective problems in robotics (with 2, 3 and 5 objectives),
web-advertising (with 3, 4 and 5 objectives) and infectious disease control (with 3 objectives), revealed that memetic
variants outperformed their original counterparts. We anticipate that the MR-POMDP along with multi-objective evolutionary
solvers will prove useful in a variety of theoretical and real-world applications.},
booktitle = {Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation},
pages = {713–720},
numpages = {8},
keywords = {multi-objective optimization, evolutionary algorithm, multi-reward pomdp},
location = {Dublin, Ireland},
series = {GECCO '11}}
Harold Soh and Yiannis Demiris
MedGEC 2011, 7th GECCO Workshop on Medical Applications of Genetic and Evolutionary Computation, 471-478, 2011
@inproceedings{10.1145/2001858.2002036,
author = {Soh, Harold and Demiris, Yiannis},
title = {Multi-Reward Policies for Medical Applications: Anthrax Attacks and Smart Wheelchairs},
year = {2011},
isbn = {9781450306904},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2001858.2002036},
doi = {10.1145/2001858.2002036},
abstract = {Medical decisions are often difficult; they involve uncertain information, multiple-objectives
and debatable outcomes. In this work, we discuss the application of the multi-reward partially-observable
Markov decision process (MR-POMDP) and NSGA2-LS, a hybridised multi-objective evolutionary solver, to two
problems in the medical domain: anthrax response and smart-wheelchair control. For the first problem, we
use a discrete model and analyse the trade-offs between the best solutions (in the form of finite-state
controllers) found by our evolutionary algorithm. For the second, we contribute an extension of our method
to the continuous space and optimising recurrent neural networks (RNNs) for use on medical robots such as
smart wheelchairs.},
booktitle = {Proceedings of the 13th Annual Conference Companion on Genetic and Evolutionary Computation},
pages = {471–478},
numpages = {8},
keywords = {multi-objective optimization, medical applications, evolutionary algorithms},
location = {Dublin, Ireland},
series = {GECCO '11}}
Harold Soh, Sonja Lim, Tianyou Zhang, Xiuju Fu, Gary Kee Khoon Lee, Terence Gih Guang Hung, Pan Di, Silvester Prakasam, Limsoon Wong
Physica A: Statistical Mechanics and its Applications 389 (24), 5852-5863, 2010
@article{SOH20105852, title = {Weighted complex network analysis of travel routes on the Singapore public transportation system},
journal = {Physica A: Statistical Mechanics and its Applications},
volume = {389},
number = {24},
pages = {5852-5863},
year = {2010},
issn = {0378-4371},
doi = {https://doi.org/10.1016/j.physa.2010.08.015},
url = {https://www.sciencedirect.com/science/article/pii/S0378437110006977},
author = {Harold Soh and Sonja Lim and Tianyou Zhang and Xiuju Fu and Gary Kee Khoon Lee and Terence Gih Guang Hung
and Pan Di and Silvester Prakasam and Limsoon Wong},
keywords = {Weighted complex network analysis, Topological analysis, Transportation system},
abstract = {The structure and properties of public transportation networks have great implications for
urban planning, public policies and infectious disease control. We contribute a complex weighted network
analysis of travel routes on the Singapore rail and bus transportation systems. We study the two networks
using both topological and dynamical analyses. Our results provide additional evidence that a dynamical
study adds to the information gained by traditional topological analysis, providing a richer view of complex
weighted networks. For example, while initial topological measures showed that the rail network is almost
fully connected, dynamical measures highlighted hub nodes that experience disproportionately large traffic.
The dynamical assortativity of the bus networks also differed from its topological counterpart. In addition,
inspection of the weighted eigenvector centralities highlighted a significant difference in traffic flows for
both networks during weekdays and weekends, suggesting the importance of adding a temporal perspective missing
from many previous studies.}}
For other publications, please see Harold’s Publications