In this talk, we explore the emergence of collaboration in multiagent reinforcement learning (MARL) through various examples, highlighting the role of human biases such as loss aversion and their impact on collaborative dynamics. We then delve into a paper co-authored by Ricard Sole and Clement Moulin-Frier, which focuses on modeling adaptive dynamics in complex ecosystems. Building on the Forest-Fire model, the study uses fire as an external, fluctuating force in a simulated environment. Agents must balance tree harvesting and fire avoidance, resulting in the evolution of an ecological engineering strategy that optimally maintains biomass while suppressing large fires. We will discuss the implications of these findings for AI management of complex ecosystems, emphasizing the potential benefits of incorporating MARL and collaboration strategies into environmental management and conservation efforts.