Abstract Submission
Introduction
Modern game-theoretic frameworks underpin our understanding of strategic behaviour across economics, biology, computer science, and complex engineered systems. As these systems scale and become increasingly mediated by computation, data, and learning algorithms, traditional equilibrium-based approaches alone are no longer sufficient. Concepts from complexity science now offer a powerful lens for analysing how macroscopic phenomena—such as cooperation, polarisation, self-organisation, instability, or sudden transitions—emerge from microscopic strategic interactions.
Evolutionary and learning-based game dynamics have become central to explaining adaptation in social and biological populations, as well as in artificial multi-agent environments. In parallel, advances such as mean-field game theory provide tractable methods for modelling very large populations, linking stochastic control, partial differential equations, and behavioural modelling at scale. Rapid progress in algorithmic game theory, mechanism design, and computational equilibrium analysis has broadened the field's reach to robotics, communications networks, distributed optimisation, and data-driven systems.
Machine learning has further propelled game theory to the forefront of modern research. Multi-agent reinforcement learning now routinely models competition and cooperation; generative and large language models increasingly display emergent strategic behaviours; and adversarial learning has strengthened ties to robustness, cybersecurity, and Stackelberg-type interactions. Across these domains, ideas from complexity science—phase transitions, metastability, chaos, and multi-stability—provide unifying principles for understanding when systems stabilise, fragment, or respond dramatically to small perturbations.
This focus session aims to unite researchers working at the intersection of game theory, complexity science, and computational modelling. We welcome contributions that introduce new theoretical frameworks, algorithms, or empirical findings; highlight cross-disciplinary connections; or showcase emerging applications in economics, biology, social systems, artificial intelligence, and complex engineered infrastructures. By fostering dialogue across these communities, we aim to deepen our understanding of modern strategic systems and chart new directions in the study of large-scale multi-agent interactions.
Session Organizers
Call for Abstracts
We welcome abstracts for contributed talks on original research exploring the games on complex systems from diverse perspectives, including methods, theories, applications, and empirical studies on the following topics related to (but not limited to):
Important Dates
| Event | Date |
|---|---|
| Abstract Submission Deadline | 17 May 2026 (Sunday) |
| Notification of Acceptance | Submissions will be reviewed on a rolling basis, and notifications of acceptance will be sent starting from 1 May 2026. |
| Focus Session | Thursday, 11 June 2026 (afternoon) |
Submission and Registration
Participants already registered for APCNCS 2026 have up till 17 May 2026 (Sunday) to submit abstracts to:
Cheong Kang Hao
Nanyang Technological University, Singapore
kanghao.cheong@ntu.edu.sgYong Ee Hou
Nanyang Technological University, Singapore
eehou@ntu.edu.sgand CC to SPMS-APCNCS2026@ntu.edu.sg
Submissions will be reviewed on a rolling basis, and notifications of acceptance will be sent starting from 1 May 2026. Early submissions are encouraged.
The programme for the focus session will be posted, and contributors notified, on 22 May 2026 (Fri). All contributors must be registered for APCNCS 2026 to participate in the focus session.
Registration Requirement
Special Issue Publication
Participants of this focus session will be invited to contribute to a special issue in MDPI Games on "Games on Complex Systems".

Ready to Submit?
Submit your abstract by 17 May 2026 to participate in this focus session