This paper investigates respiratory odor navigation with minimal evolutionary robots. We introduce a novel agent tasked with locating a chemical source solely through the use of a respiratory sensor, a challenge inspired by the active sampling strategies observed in a wide variety of animals (e.g., sniffing, whisking). Prevailing hypotheses suggest that odor navigation serves predominantly to gate behaviors in response to information gleaned from different sensory modalities. We analyze the agent’s behavior and neural dynamics using dynamical systems theory, demonstrating the possibility of strategies that instead rely solely on the information obtained from their respiratory sensor. Our findings reveal that agents can successfully locate chemical sources through the synchronization of breathing rates with motor outputs, mirroring sensorimotor coupling strategies recently identified in the experimental literature. This research contributes to the theoretical understanding of sensory odor navigation and the role of physiology in agent-environment interactions.

In their most abstract form, we can understand tissues as being composed of three general cell types: stem cells, transit-amplifying cells, and differentiated cells. Additionally, we know that these cell types can secrete molecules or regulatory factors that can exert control over other cell populations. Recent work in theoretical biology examined several cell lineage control networks that result in tissue homeostasis. We develop an alternative mass action model that views developmental cell lineages as biological pathways. We demonstrate that three cell lineages are homeostatic irrespective of the implementation and that their control structures exhibit a degeneracy, containing solely negative feedback or negative resistance. We replicate and extend the homeostatic control architectures previously outlined and report on the relevant bifurcations and dynamics of these pathways.