5th Collaborative Workshop on Modeling Collective Behavior

Where: The University of Texas at Austin, Austin, TX

When: September 16-18, 2022

Organizers: James Curley (UT Austin), Jason Graham (Scranton University) & Simon Garnier (NJIT)

Funding: NSF OAC Public Access Initiative grant #1838955

If you are interested to propose a project, please email Jason Graham at jason.graham@scranton.edu.

Application deadline: TBD

The goal of this workshop is to provide researchers coming from mathematics, physics, engineering and biology with experience in working collaboratively to model and analyze data produced by research in collective behavior.

During the workshop, interdisciplinary teams will work toward constructing mathematical and/or computational models of biological data. Each team will be tasked with exploring, analyzing and modeling original data sets provided by biologist attendees. The event will be similar in spirit to a hackathon in computer science, with the goal of finding new ways to understand the provided biological data. Regular debriefing sessions will be organized throughout the 3 days of the workshop in order for each team to provide updates to and receive feedback from the rest of the participants on their progress.

This should provide valuable training and experience for researchers coming from all fields, as well as an opportunity to create new collaborations beyond the workshop itself. Ultimately, we hope this workshop to impact research on collective animal and human behavior by promoting close collaboration between scientists working on understanding the organization and functioning of animal and human societies.

Space is limited. In addition to the project leaders below, we will recruits between 10 and 15 participants. Funding for travel and housing is available courtesy of the NSF OAC Public Access Initiative grant #1838955; the amount will be determined based on the number of participants and the cost of traveling to Austin for each of them.

Information about travel and housing will be soon indicated at the bottom of this page.

Project list:

Project 1: (leaders: Emerson Arehart, Rishita Das)

There are often complex tradeoffs between personal and public goods. In many cases, it can seem impossible to transition out of behavioral paradigms with benefits for individuals but negative effects on the collective. We consider the persistence of private transportation (driving) when a different paradigm (bicycling) offers greater benefits for individuals and the collective, given that enough individuals participate.

We consider a hypothetical city which must allocate resources to either automobile or bicycle infrastructure, and a population of commuters who either drive or bike to work. Individual commuters seek to maximize benefit to themselves, but receive benefit directly (exercise, cost, safety) and from an environmental common-pool resource - air quality. Air quality depends on the proportion of individuals biking vs driving, but affects cyclists and drivers differently. Individuals have access to information about their fellow citizens, such as the proportion of bikers vs drivers, and may use this information in deciding mode of transportation. Finally, infrastructure changes - for example, reallocating roadways from car lanes to bike lanes - happen at certain thresholds, changing the reward structure for bikers and drivers.

We analyze this system in the context of eco-evolutionary game theory to understand the relationship between individual and collective incentive structures, with the aim of understanding how certain parameters could be tuned to incentivize the transition from driving to bicycling. We examine data from driving - biking transitions in Copenhagen and Paris, as well as biking to driving transitions in China, in the hopes of parameterizing and testing our model and finding future directions for refining our approach.

Project 2: Coupled Dynamics between Collective Human Behavior and Infection Spread (leaders: Changqing Cheng, Daniel Strömbom)

The COVID-19 pandemic has underscored the impact of collective human behaviors on the infection spreading, including human mobility, adherence to government intervention policies as well as behavior imitation on the social media platform. Thus, it is indispensable to study the interplay between such collective human behavior and infection evolution for optimal policy design. In this project, we will build game-theoretic model to simulate such interconnected dynamics.

Build a multi-layer network to represent disjoint communities, on each of which a susceptible-exposed-infectious-recovered (SIER) model is imposed to simulate the infection propagation.
Human mobility will take place across adjacent communities according to government policy and collective adherence to such policies.
Imitation of behavioral adaption in response to the infection prevalence between agents on the social network layer, even the agents may be dispersed across remote communities. Facebook network data will be provided.
Study the coordinated and uncoordinated intervention policies across the communities.
Study the time delay effect in information dissemination (e.g., the prevalence rate, when to enact the policy).

Project 3: Modeling complex physically entangled behavior of aquatic worms (leaders: Saad Bhamla, Harry Tuazon)

Many organisms live in the air-water interface. Previously, we have explored a physically entangled collective that can utilize surface properties of their tails to take advantage of the water’s interface. We explored the potential function and mechanism of the California blackworm (Lumbriculus variegatus) worm “buoy”, which is comprised of a floating population of negatively buoyant entangled blackworms on the water side of the interface. This phenomenon is similar to the floating ant rafts formed on the air side of the interface. In nature, blackworms (length 20-40 mm and diameter 0.5 mm) dwell in benthic regions where they burrow their heads downwards in the substrate and raise their tails vertically upwards. They are found in shallow anoxic regions of freshwater systems, which contain low levels of dissolved oxygen (<2 mg/L). Although they can breathe using their mucous body, blackworms supplement oxygen respiration using their ciliated tails, which stretched horizontally along the water surface. Its tail contains an alternating pattern of hydrophilic intersegments and hydrophobic segments, where the hydrophobic portions provide a stabilizing upward force as it dewets on the interface. We estimate that an average worm weighing 7 mg (in air) support itself by exposing about 1 patterned segment on the interface. As more and more blackworms entangle with one another, the collective’s center of mass shifts upwards until they lift off from the ground, creating a buoy-like structure. The goal of this project is to explore and analyze this new entangled collective behavior using mathematical and computational models.

Confirmed participants (so far):

TBD

General schedule of the workshop:

TBD

Workshop location, parking and travel information

More information to come later.