UROL:EN Emergent Energetic Regulation in Dynamic Biological Networks

Regulation mechanisms are essential for keeping systems within desired working conditions. For instance, body temperature in humans is regulated by a complex network of neurons and hormones that control heat production (e.g., through metabolic activity) and loss (e.g., through sweating) to avoid fatal hypo- or hyperthermia. Typical biological and engineered regulation mechanisms take the form of circuits that connect sensors to actuators in a predictable way (e.g., a thermostat in an air conditioning system).

However, systems that are composed of many loosely connected and mobile units (e.g., a colony of ants or a fleet of autonomous robots) rarely exhibit long-lasting connections that could support such rigid regulatory circuits. In this context, this collaborative research brings together biologists, theoreticians, and engineers to achieve two goals: understand how highly plastic collective systems regulate themselves in the face of changes (using energetic regulation in ants as a model system), and derive general principles to engineer artificial distributed systems that can autonomously regulate their collective activities to maintain function in uncertain environments.

The project will also give students ranging from K-12 to Ph.D. an opportunity to learn how social systems succeed and fail at regulating themselves, and how fundamental knowledge of natural processes can lead to new technological developments and applications in engineering.

The project has three complementary components. In Component 1, the researchers will perform laboratory experiments with ants to investigate whether biological collectives exhibit energetic regulation in response to both weak and strong variations in energy demand and availability, and how this impacts their biological productivity. These studies will combine computer vision-assisted behavioral observations to measure the individual and collective behaviors of the ants and physiological measurements to determine the dynamics of their energetic states.

In Component 2, the result of the laboratory experiments will be used to develop a network-theoretic framework to elucidate and engineer energetic regulation in distributed and highly dynamic collectives of self-organizing units. The goal will be to design generalizable abstractions that allow for theoretical analysis to determine what behavioral rules lead to successful collective regulation or to its failure.

Finally, in Component 3, the researchers will design engineering solutions for collective energy management in robotic swarms and evaluate their efficiency in simulations and in experiments with actual robots. The goal is to build a swarm that will be capable of optimally balancing energetic supply and demand, even in dynamical and unpredictable working environments.

Ultimately, this effort will lead to establishing a new paradigm for better understanding how loosely connected units can nonetheless collectively maintain function and homeostasis, despite experiencing fluctuations in their energetic requirements and/or their ability to exploit resources.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.