Experiments on Concurrent Artificial Environment

We show how the simulation of concurrent system is of interest for both behavioral studies and strategies of learning applied on prey-predator problems. In our case learning studies into unknown environment have been applied to mobile units by using genetic algorithms (GA). A set of trajectories, generated by GA, are able to build a description of the external scene driving a predators to a prey. Here, an example of prey-predator strategy,based on field of forces, is proposed. The evolution of the corespondent system can be formalized as an optimization problem and, for that purpose, GA can be use to give the right solution at this problem. This approach could be applied to the autonomous robot navigation in risky or inaccessible environments (monitoring of atomic power plants, exploration of sea bottom, and space missions).