Chaoran Chen School of Computer Science, Zhuhai College of Science and Technology, Zhuhai 519041, China Computational Ecology and Software ISSN 2220-721X http://www.iaees.org/publications/journals/ces/online-version.asp 2026 16 3 210 219 International Academy of Ecology and Environmental Sciences Hong Kong 23 January 2026 27 February 2026 1 September 2026 cellular automata forest fire modeling multi-agent systems wildfire suppression complex systems spatial dynamics Forest fires are complex spatiotemporal phenomena influenced by local interactions, environmental conditions, and human intervention. In this study, we propose a hybrid modeling framework that integrates a probabilistic cellular automaton (CA) for fire propagation with mobile intelligent agents for active suppression. The fire dynamics are governed by neighbor-dependent stochastic rules modulated by vegetation density and wind intensity, while suppression agents dynamically move toward burning sites and probabilistically extinguish fires. We conduct systematic multi-scenario experiments to examine (1) the impact of wind speed, (2) vegetation density, and (3) the number of suppression agents on fire evolution. Results reveal nonlinear relationships between these parameters and suppression efficiency, including threshold effects and diminishing returns in agent scaling. The model demonstrates how spatial structure, stochasticity, and adaptive control jointly shape fire outcomes. Our framework provides a flexible platform for studying coupled human-environment dynamics and offers insights into optimal resource allocation for wildfire management. http://www.iaees.org/publications/journals/ces/articles/2026-16(3)/a-cellular-automaton-agent-hybrid-model.pdf