Improved performance of naïve creature learning to cross a highway

We present a model of simulated naïve creatures learning to cross a highway. The creatures are able to learn by “imitating what works and avoiding what does not work”. Our simulations show that the creatures´ population success in learning to cross a single-lane unidirectional highway is influenced by the conditions of the environment; i.e. by the car traffic density, presence or not of “erratic drivers”, and by the selection of a crossing point location on the highway. The creatures´ population success of crossing the highway can be improved by allowing the creatures to move randomly along the edge of the highway to find a safer location to cross from, and by preserving the knowledge base from environment with lower car traffic density to the one with higher car traffic density.