In this paper, we describe and test a simple algorithm for enabling a single drone to herd a flock of birds away from a dangerous area in which birds may collide with an airplane. To do this, a drone suddenly approaches the flock from beneath, when the flock comes close to the runway. This makes the birds change their path to a higher elevation and safely pass the runway. A simulation platform for evaluating the success of different scenarios regarding this method was created based on Reynolds’ flocking rules. The results showed the possibility of this method to be successful when the drone has a climbing speed suitable for any particular flying speed of birds. In addition to flying speeds, how scattered the birds are in the flock is also another factor that was investigated in the simulations. It turned out that the success of preventing bird strikes may reduce when birds are flying at a far distance from each other.

We implement Varela, Maturana and Uribe's original autopoiesis algorithm with suitable modifications as proposed by McMullin. We further investigate how environmental factors affect formation of autopoietic entities - namely how long an entity remains a whole after formation and to what size does it grow in its life span i.e. Life span and Cycle size respectively. We find that ratios of different basic elements like Holes, Substrates and Catalysts do not affect Life span and Cycle size meaningfully but both properties are affected negatively if disintegration probability—the probability of a Link element to transform into a Substrate element—is increased.

As we endow cognitive robots with ever more human-like capacities, these have begun to resemble constituent aspects of the ‘self’ in humans (e.g., putative psychological constructs such as a narrative self, social self, somatic self and experiential self ). Robot’s capacity for body-mapping and social learning in turn facilitate skill acquisition and development, extending cognitive architectures to include temporal horizon by using autobiographical memory (own experience) and inter-personal space by mapping the observations and predictions on the experience of others (biographic reconstruction). This ‘self-projection’ into the past and future as well as other’s mind can facilitate scaffolded development, social interaction and planning in humanoid robots. This temporally extended horizon and social capacities newly and increasingly available to cognitive roboticists have analogues in the function of the Default Mode Network (DMN) known from human neuroscience, activity of which is associated with selfreferencing, including discursive narrative processes about present moment experience, ‘self-projection’ into past memories or future intentions, as well as the minds of others. Hyperactivity and overconnectivity of the DMN, as well as its co-activation with the brain networks related to affective and bodily states have been observed in different psychopathologies. Mindfulness practice, which entails reduction in narrative self-referential processing, has been shown to result in an attenuation of the DMN activity and its decoupling from other brain networks, resulting in more efficient brain dynamics, and associated gains in cognitive function and well-being. This suggests that there is a vast space of possibilities for orchestrating self-related processes in humanoids together with other cognitive activity, some less desirable or efficient than others. Just as for humans, relying on emergence and selforganization in humanoid scaffolded cognitive development might not always lead to the ‘healthiest’ and most efficient modes of cognitive dynamics. Rather, transient activations of self-related processes and their interplay dependent on and appropriate to the functional context may be better suited for the structuring of adaptive robot cognition and behaviour.

Being able to measure time, whether directly or indirectly, is a significant advantage for an organism. It permits it to predict regular events, and prepare for them on time. Thus, clocks are ubiquitous in biology. In the present paper, we consider the most minimal abstract pure clocks and investigate their characteristics with respect to their ability to measure time. Amongst other, we find fundamentally diametral clock characteristics, such as oscillatory behaviour for local time measurement or decay-based clocks measuring time periods in scales global to the problem. We include also cascades of independent clocks (“clock bags”) and composite clocks with controlled dependency; the latter show various regimes of markedly different dynamics.