Why animals swirl and how they group

We report a possible solution for the long-standing problem of the biological function of swirling motion, when a group of animals orbits a common center of the group. We exploit the hypothesis that learning processes in the nervous system of animals may be modelled by reinforcement learning (RL) and apply it to explain the phenomenon. In contrast to hardly justified models of physical interactions between animals, we propose a small set of rules to be learned by the agents, which results in swirling. The rules are extremely simple and thus applicable to animals with very limited level of information processing. We demonstrate that swirling may be understood in terms of the escort behavior, when an individual animal tries to reside within a certain distance from the swarm center. Moreover, we reveal the biological function of swirling motion: a trained for swirling swarm is by orders of magnitude more resistant to external perturbations, than an untrained one. Using our approach we analyze another class of a coordinated motion of animals—a group locomotion in viscous fluid. On a model example we demonstrate that RL provides an optimal disposition of coherently moving animals with a minimal dissipation of energy.

Why Do Animals Swirl and How Do They Group?

We report a possible solution for the long-standing problem of the biological function of swirling motion, when a group of animals orbits a common center of the group. We exploit the hypothesis that learning processes in the nervous system of animals may be modelled by reinforcement learning (RL) and apply it to explain the phenomenon. In contrast to hardly justified models of physical interactions between animals, we propose a small set of rules to be learned by the agents, which results in swirling. The rules are extremely simple and thus applicable to animals with very limited level of information processing. We demonstrate that swirling may be understood in terms of the escort behavior, when an individual animal tries to reside within a certain distance from the swarm center. Moreover, we reveal the biological function of swirling motion: a trained for swirling swarm is by orders of magnitude more resistant to external perturbations, than an untrained one. Using our approach we analyze another class of a coordinated motion of animals – a group locomotion in viscous fluid. On a model example we demonstrate that RL provides an optimal disposition of coherently moving animals with a minimal dissipation of energy.

Finite-Time Thermodynamics in Economics

In this paper, we consider optimal trading processes in economic systems. The analysis is based on accounting for irreversibility factors using the wealth function concept. The existence of the welfare function is proved, the concept of capital dissipation is introduced as a measure of the irreversibility of processes in the microeconomic system, and the economic balances are recorded, including capital dissipation. Problems in the form of kinetic equations leading to given conditions of minimal dissipation are considered.

Inherited learning in a system of minimum dissipation: The case of the Yumhu of Ixtenco-Mexico

Introduction This article aims to show the way in which a social system of minimum dissipation -like the Yumhu of Ixtenco- has the capacity to counteract its entropic levels avoiding reaching thermal death, due to the type of non-formal learning that is developed in this and its way of reproducing. In this regard, Objective was to identify the forms of non-formal learning in the social system of minimum dissipation of the Yumhu of Ixtenco that in a contrasting, dynamic and changing environment has been able to provide the Yumhu adapt and survive in time despite the weakening of its energy potential. Materials and methodsused was qualitative with ethnographic tools applied to seven research subjects. The main Results point to the fact that non-formal learning in the Yumhu system happens under the principles of an indigenous pedagogy of low dissipation, which allows the survival of the system. The main Conclusions are that learning takes place from an inherited base that the Yumhu have used to preserve themselves over time, due to their functioning as a minimal dissipation system, which weakens their energetic potential (such as information) Discussion in proportion to their input flows, which allows them to adapt to their context with minimal energy reaching a stable state.