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It is to date an open question to know how the updating methods affect the evolution of a multi-agent system. This question has been tackled for various complex systems such as cellular automata, Boolean networks, neural networks but little is known for multi-agent systems, especially for the models with a complex behaviour which emerges from simple local rules. This paper focuses on a multi-turmite model, namely the multiple Langton's ants model. All the agents are updated simultaneously and the variation of the updating scheme consists only in choosing different strategies for solving the conflicts produced when two or more agents want to go on the same location. We show that for the same formulation of the agents' behaviour, and the same initial conditions, the use of different updating schemes may lead to qualitatively different evolutions of the system. As a positive spin-off of this study, we exhibit new phenomena of the multi-turmite model such as deadlocks or gliders.

How important are updating schemes in multi-agent systems? An illustration on a multi-turmite model