Social interactions shape our lives. Yet, their complexity vastly reduces our ability to understand, model, and even mimic optimal social network structures. The recent advent of physics of behavior studies is providing new insights to social interactions that are governed by physical principles: from short-range interactions, e.g. plants that utilize the infra-red visual spectrum to distinguish shade producing plants from inanimate objects to long-range interactions, e.g. insect swarms who harness air-flow fields to coordinate thermoregulation.
This Research Topic will explore the boundary between such animate and related inanimate physical interactions, how social interactions are governed by physics, and vice versa, how other interactions between entities we tend to consider as inanimate could be social. We will draw from a diverse range of efforts to address it, including experimental work as well as theoretical, computational, and robotic models.
The idea for this Research Topic was fueled by a discussion on “What makes behavior social?” at the 2018 Aspen Center for Physics (ACP) Workshop on Physics of Behavior, and at the 2020 American Physical Society (APS) March meeting, where the boundary between inanimate and animate physical interactions was explored.
Our goal is to provide a home for publications emerging from these discussions, as well as ongoing and new work in this sub-field.
We welcome Original Research and Reviews to advance knowledge on the following topics:
? How social interactions are manifested by the behavioral physics of an individual, and the physics of the environmental medium through which social interactions occur.
? Application of Statistical Physics and Machine Learning techniques to identifying behavioral rules from large experimental datasets.
We will consider social interactions occurring within a range of group sizes, from small groups to collective behavior. We will consider a diverse range of efforts, including experimental work as well as theoretical, computational, and robotic models.
Social interactions shape our lives. Yet, their complexity vastly reduces our ability to understand, model, and even mimic optimal social network structures. The recent advent of physics of behavior studies is providing new insights to social interactions that are governed by physical principles: from short-range interactions, e.g. plants that utilize the infra-red visual spectrum to distinguish shade producing plants from inanimate objects to long-range interactions, e.g. insect swarms who harness air-flow fields to coordinate thermoregulation.
This Research Topic will explore the boundary between such animate and related inanimate physical interactions, how social interactions are governed by physics, and vice versa, how other interactions between entities we tend to consider as inanimate could be social. We will draw from a diverse range of efforts to address it, including experimental work as well as theoretical, computational, and robotic models.
The idea for this Research Topic was fueled by a discussion on “What makes behavior social?” at the 2018 Aspen Center for Physics (ACP) Workshop on Physics of Behavior, and at the 2020 American Physical Society (APS) March meeting, where the boundary between inanimate and animate physical interactions was explored.
Our goal is to provide a home for publications emerging from these discussions, as well as ongoing and new work in this sub-field.
We welcome Original Research and Reviews to advance knowledge on the following topics:
? How social interactions are manifested by the behavioral physics of an individual, and the physics of the environmental medium through which social interactions occur.
? Application of Statistical Physics and Machine Learning techniques to identifying behavioral rules from large experimental datasets.
We will consider social interactions occurring within a range of group sizes, from small groups to collective behavior. We will consider a diverse range of efforts, including experimental work as well as theoretical, computational, and robotic models.