Maps are useful for navigation if (i) there is adequate known detail provided on the map, (ii) your present location on the map is known as is (iii) the location of your goal. Many natural examples of successful navigation, such as seasonal bird migration across continents and oceans, lack some or all of these. Success requires some strategy for continuously governing the direction of movement according to continuous sampling of available sensory cues. If sensory cues are strictly local, an instantaneous snapshot often gives insufficient guidance on the course to steer. Some form of active perception is needed, where motion gives rise to cues as to whether the current course needs to change. We illustrate with one old and two novel examples of increasing complexity: (A) Run-and-Tumble strategies, such as used by e. Coli , allowing the detection of local gradients. (B) Swerve-Zone, a novel artificial life model of bird migration showing how region-wide cues, even in the absence of discernible local gradients, can nevertheless still guide. And (C) Parting-the-Waves, a proposed strategy for exploiting the wave patterns underlying long-distance steering as used by Micronesian navigators, showing how the boat motion is essential for discriminating between swells. All three depend on some default motion; when stationary, you cannot sense where the goal lies. They exploit motion in different ways, but all simplify navigational search into tractable forms apparently amenable to evolution.

This paper describes a potentially rewarding research program aimed at designing, modeling, analyzing and experimentally realizing artificial cells in the wetware domain endowed with a ‘neural network’-like module for achieving minimal perception. In particular, we present a possible implementation based on bacterial phosphorylation signaling networks (dubbed as “phospho-neural network” by Hellingwerf and collaborators in 1995 ). At this initial stage only preliminary discussions are possible. The scenario we devise minimizes unrealistic assumptions and it is based on the state-of-the-art of contemporary artificial cell technology. This contribution is intended as a plan to forster the construction and the theoretical analysis of next-generation artificial cells.

We emulated an experiment that shows the Einstellung-effect by building an agent-based model and developed a new heuristic that helps to overcome the effect.