L. Dagorn, M. Petit, J.M. Stretta, X. Bernardet and A.G. Ramos
The aim of this paper is to introduce the study of the eco-ethology of tropical tuna using asynthetic approach (Artificial Life and Artificial Intelligence). Two different models are proposed dealing with tuna schooling behaviour and distribution of tuna schools in the environment. The first model uses a genetic algorithm which is an optimisation technique born from the Darwinian concept of evolution. The aim is to find optimal behaviour (movement and schooling behaviour) for artificial tuna populations living in heterogeneous and dynamic environments. The results are discussed according to knowledge on real schooling behaviour.The second model is based on the ideal free distribution theory for tuna schooling behaviour to describe the possible distribution and migration of animals in a heterogeneous habitat. It is pointed out that simple behavioural sequences can manage an artificial tuna population: tuna schooling evolves depending on both the energetic rate and the biological and physical environment. These models represent examples of possible computational experiments which must be completed with real experiments at sea.