Siang Yew Chong

Contact

• workMalaysia Campus
  Jalan Broga
  43500 Semenyih
  Selangor Darul Ehsan
  Malaysia
• work+6 (03) 8924 8148
• siang-yew.chong@nottingham.edu.my
• https://www.cs.bham.ac.uk/~szc

Biography

Dr. Chong is an Associate Professor with the School of Computer Science, University of Nottingham Malaysia Campus. He is a member of the Automated Scheduling, Optimization and Planning Research Group, School of Computer Science, University of Nottingham, UK. He was a Marie Sklodowska-Curie Fellow (2016-2018) and currently an Honorary Research Fellow with the School of Computer Science, University of Birmingham, UK .

Teaching Summary

2019-2020:

Advanced Algorithms and Data Structures

Project in Advanced Algorithms and Data Structures

Machine Learning (20 Credits)

Simulation and Optimisation for Decision Support (20 Credits)

Fundamentals of Artificial Intelligence (Compulsory)

Previously:

Advanced Algorithms and Data Structures

Project in Advanced Algorithms and Data Structures

Simulation and Optimisation for Decision Support (20 Credits)

Fundamentals of Artificial Intelligence (Compulsory)

Mathematics for Computer Scientists (Compulsory)

Machine Learning

Research Summary

Main Underlying Research Theme -- Understanding complex real-world strategic decision-making systems naturally as models that involve populations of learning agents (coevolutionary systems):

Unified Framework for Complex Coevolutionary Systems -- Uncover principle structures underlying agent behaviors (digraph theory) through sampling processes modeling agent learning (Markov chains) for precise characterizations of coevolution.

Complete Characterization of Complex Coevolutionary Dynamics -- Develop new tools to study coevolutionary systems that generate complex (including chaotic) dynamics (dynamical systems theory).

Emergence of Macro-scale Behaviors from Micro-scale structures -- (Multi-agent systems) simulation to study micro-scale conditions giving rise to macro-scale behaviors (evolution to cooperation) with nonlinear behavioral representation (neural networks).

Selected Publications

• S. Y. CHONG, P. TINO and J. HE, 2019. Coevolutionary Systems and PageRank Artificial Intelligence. (In Press.)
• S. Y CHONG, P. TINO, J. HE and X. YAO, 2019. A New Framework for Analysis of Coevolutionary Systems - Directed Graph Representation and Random Walks Evolutionary Computation. 27(2), 195-228
• P. TINO, S. Y. CHONG and X. YAO, 2013. Complex Co-evolutionary Dynamics - Structural Stability and Finite Population Effects IEEE Transactions on Evolutionary Computation. 17(2), 155-164
• S. Y. CHONG, P. TINO, D. C. KU and X. YAO, 2012. Improving Generalization Performance in Co-evolutionary Learning IEEE Transactions on Evolutionary Computation. 16(1), 70-85

• View all publications

• S. Y CHONG, P. TINO, J. HE and X. YAO, 2019. A New Framework for Analysis of Coevolutionary Systems - Directed Graph Representation and Random Walks Evolutionary Computation. 27(2), 195-228
• S. Y. CHONG, P. TINO and J. HE, 2019. Coevolutionary Systems and PageRank Artificial Intelligence. (In Press.)
• Y. M. LEE, S. Y. CHONG, K. GOONTING and E. SHEPPARD, 2017. The Effect of Speed Limit Credibility on Drivers' Speed Choice Transportation Research Part F. 45, 43-53
• C. W. KHENG, D. C. KU, H. F. NG, M. KHATTAB and S. Y. CHONG, 2016. Curvature Flight Path for Particle Swarm Optimisation In: Genetic and Evolutionary Computation Conference 2016 (GECCO'16). 29-36
• N. R. SABAR, S. Y. CHONG and G. KENDALL, 2015. A Hybrid Differential Evolution Algorithm–Game Theory for the Berth Allocation Problem In: Proc. of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems. 2. 77-87
• J. Y. TEY, R. RAMLI, C. W. KHENG, S. Y. CHONG and M. A. Z. ABIDIN, 2014. Identification of Vehicle Suspension Parameters by Design Optimization Engineering Optimization.
• A. PELETEIRO, J. C. BURGUILLO and S. Y. CHONG, 2014. Exploring Indirect Reciprocity in Complex Networks Using Coalitions and Rewiring In: Proc. of the 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014). 669-676
• T. H. MAUL, A. BARGIELA, S. Y. CHONG and A. S. ADAMU, 2014. Towards Evolutionary Deep Neural Networks In: Proc. of the 28th European Conference on Modelling and Simulation (ECMS 2014). 319-325
• D. ASHLOCK, G. KENDALL and S. Y. CHONG, 2013. Guest Editorial: Special Issue on Understanding Complex Evolutionary Systems IEEE Transactions on Evolutionary Computation. 17(2), 153-154
• P. TINO, S. Y. CHONG and X. YAO, 2013. Complex Co-evolutionary Dynamics - Structural Stability and Finite Population Effects IEEE Transactions on Evolutionary Computation. 17(2), 155-164
• S. Y. CHONG, P. TINO, D. C. KU and X. YAO, 2012. Improving Generalization Performance in Co-evolutionary Learning IEEE Transactions on Evolutionary Computation. 16(1), 70-85
• C. W. KHENG, S. Y. CHONG and M. H. LIM, 2012. Centroid-Based Memetic Algorithm: Adaptive Lamarckian and Baldwinian Learning International Journal of Systems Science. 43(7), 1193-1216
• D. GAIROLA and S. Y. CHONG, 2012. An Economics-Inspired Noise Model in Spatial Games with Reputation. In: J. KOLODZIEJ, S. U. KHAN and T. BURCZYNSKI, eds., Advances in Intelligent Modeling and Simulation: Artificial Intelligence-based Models and Techniques in Scalable Computing
• P. TINO, S. Y. CHONG and X. YAO, 2010. On Reliability of Simulations of Complex Co-evolutionary Process In: Proc. of the 24th European Conference on Modelling and Simulation (ECMS 2010), 1-4 June, 2010, Kuala Lumpur, Malaysia. 258-264
• C. W. KHENG, M. H. LIM and S. Y. CHONG, 2010. A Study on Lamarckian and Baldwinian Learning on Noisy and Noiseless Landscapes In: Proc. of the 24th European Conference on Modelling and Simulation (ECMS 2010), 1-4 June, 2010, Kuala Lumpur, Malaysia. 323-329
• C. W. KHENG, S. Y. CHONG and A. BARGIELA, 2009. Multi-resolution Optimisation: Application of Meta-heuristic in Function Remodelling In: Proc. of the 23rd European Conference on Modelling and Simulation (ECMS 2009), 9-12 June, 2009, Madrid, Spain. 834-840
• S. Y. CHONG, C. HILL and X. YAO, 2009. Co-evolutionary Learning of Contextual Asymmetric Actors In: Proc. of the 23rd European Conference on Modelling and Simulation (ECMS 2009), 9-12 June, 2009, Madrid, Spain.. 827-833
• S. Y. CHONG, P. TINO and X. YAO, 2009. Relationship Between Generalization and Diversity in Co-evolutionary Learning IEEE Transactions on Computational Intelligence and AI in Games. 1(3), 214-232
• S. Y. CHONG, P. TINO and X. YAO, 2008. Measuring Generalization Performance in Co-evolutionary Learning IEEE Transactions on Evolutionary Computation. 12(4), 479-505
• S. Y. CHONG, J. HUMBLE, G. KENDALL, J. LI and X. YAO, 2007. Iterated Prisoner's Dilemma and Evolutionary Game Theory. In: G. KENDALL, X. YAO and S. Y. CHONG, eds., The Iterated Prisoners' Dilemma: 20 Years On World Scientific Press, Singapore. 23-62
• S. Y. CHONG and X. YAO, 2007. Multiple Choices and Reputation in Multiagent Interactions IEEE Transactions on Evolutionary Computation. 11(6), 689-711
• S. Y. CHONG, J. HUMBLE, G. KENDALL, J. LI and X. YAO, 2007. Learning IPD Strategies through Co-evolution. In: G. KENDALL, X. YAO and S. Y. CHONG, eds., In The Iterated Prisoners' Dilemma: 20 Years On World Scientific Press, Singapore. 63-87
• S. Y. CHONG, J. HUMBLE, G. KENDALL, J. LI and X. YAO, 2007. The Iterated Prisoner's Dilemma: 20 Years On. In: G. KENDALL, X. YAO and S. Y. CHONG, eds., The Iterated Prisoner's Dilemma: 20 Years On World Scientific Press, Singapore. 1-21
• G. KENDALL, X. YAO and S. Y. CHONG, eds., 2007. The Iterated Prisoners' Dilemma: 20 Years On World Scientific Press, Singapore.
• C. M. FRAYN, A. N. PRYKE and S. Y. CHONG, 2006. Exploring the Effect of Proximity and Kinship on Mutual Cooperation in the Iterated Prisoner's Dilemma In: Proc. of the 9th International Conference on Parallel Problem Solving from Nature (PPSN IX), Lecture Notes in Computer Science, Vol. 4193, Reykjavik, Iceland, 2006. 701-710
• S. Y. CHONG and X. YAO, 2006. Evolving Cooperation in Complex Behavioral Interactions through Reputation. In: G. G. YEN and D. B. FOGEL, eds., In Computational Intelligence: Principles and Practice IEEE Press. 237-256
• S. Y. CHONG and X. YAO, 2006. Self-Adapting Payoff Matrices in Repeated Interactions In: Proc. of the 2006 IEEE Symposium on Computational Intelligence and Games (CIG 2006), IEEE Press, Piscataway, NJ, USA, 22-24 May 2006, Reno/Lake Tahoe, Nevada, USA. 103-110
• S. Y. CHONG and X. YAO, 2005. Behavioral Diversity, Choices, and Noise in the Iterated Prisoner's Dilemma IEEE Transactions on Evolutionary Computation. 9(6), 540-551
• S. Y. CHONG, M. K. TAN and J. D. WHITE, 2005. Observing the Evolution of Neural Networks Learning to Play the Game of Othello IEEE Transactions on Evolutionary Computation. 9(2), 240-251
• S. Y. CHONG and X. YAO, 2004. The Impact of Noise on Iterated Prisoner's Dilemma with Multiple Levels of Cooperation In: Proc. of the 2004 Congress on Evolutionary Computation (CEC 2004), IEEE Press, Piscataway, NJ, USA, 19-23 June 2004, Portland, Oregon, USA. 348-355
• S. Y. CHONG, D. C. KU, H. S. LIM, M. K. TAN and J. D. WHITE, 2003. Evolved Neural Networks Learning Othello Strategies In: Proc. of the 2003 Congress on Evolutionary Computation (CEC 2003), IEEE Press, Piscataway, NJ, USA, 8-12 December 2003, Canberra, Australia. 2222-2229