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Humans have been able to tackle biosphere complexities by acting as ecosystemengineers, profoundly changing the flows of matter, energy and information.This includes major innovations that allowed to reduce and control the impactof extreme events. Modelling the evolution of such adaptive dynamics can bechallenging given the potentially large number of individual and environmentalvariables involved. This paper shows how to address this problem by using fireas the source of external, bursting and wide fluctuations. Fire propagates on aspatial landscape where a group of agents harvest and exploit trees whileavoiding the damaging effects of fire spreading. The agents need to solve aconflict to reach a group-level optimal state: while tree harvesting reducesthe propagation of fires, it also reduces the availability of resourcesprovided by trees. It is shown that the system displays two major evolutionaryinnovations that end up in an ecological engineering strategy that favours highbiomass along with the suppression of large fires. The implications forpotential A.I. management of complex ecosystems are discussed.

Cooperative control of environmental extremes by artificial intelligent agents