Welcome to the Morsky Lab website. We work at the crossroads of mathematics, biology, and social science. Lab members are primarily interested in understanding biological and social systems through mathematical modelling. Much of this work focuses on the evolution of cooperation in a variety of settings, such as human communities, cancer, and infectious diseases. Additionally, many biological and abiological systems are heavily impacted by human behaviour, and so incorporating behaviour into such models is critical in understanding their dynamics. To study such systems, we frequently employ a game theoretic framework that features social dilemmas. We are interested in cases where social dilemmas arises, how they arise, and how they may be ameliorated.
The lab is currently accepting graduate students. Information for prospective graduate students can be found on the Department's website. For current FSU grad students, please send an email to Bryce Morsky at firstname.lastname@example.org. Informal inquiries are welcome. A strong background in and enthusiams for mathematical or computational theory in ecology, evolution, and/or social science is ideal. There are a great variety of complex biological and social systems that we can explore.
We are broadly interested in sociality in humans: the role of social norms, human rationality, group formation, collective identity, and social diversity. Theory can address these topics and has roles in understanding the dynamics of human society with applications to social policy. Our work in this field has addressed questions such as group formation through homophilic imitation and through dishonest signalling, and the emergence of normative meaning. Social coordination can be attained through the emergence of shared social norms, which occurs through an evolutionary process acting like a blind choreographer, analogous to Dawkins’ blind watchmaker [journal]. Such social norms can be predicated on natural events that have no inherent meaning. And yet, normative meaning that coordinates society can emerge (more technically speaking, the system can evolve to a correlated equilibrium).
The spread of pathogens in human populations crucially depends on social, political, psychological, and economic factors. They can impact the efficacy of treatment and public policy through their effects on human behaviour. Social norms, cultural practices, and laws, both formal and informal, pressed by political and social institutions are examples. These and other behavioural factors may promote or inhibit the spread of disease, and thus have implications for public policy. Events of this past year have demonstrated with unusual force how critical the interactions between social and epidemiological dynamics are to controlling disease, and how much we still have to learn about them. We are interested in understing how policy and the various social, economic, and biological components of disease impact one another. With this understanding, we can design policies to best mitigate disease.
Cancer and bacteria can produce public goods that are prone to being taken advantage of by free-riders. Examples include angiogenic factors in tumours, and siderophore production in bacteria. Because cheaters do not pay the cost of production of these goods, they have more energy to compete against altruists. Cheaters thus seem to be detrimental to the tumour. However, the presence of cheaters can benefit the tumour as a whole in overcoming the immune response [journal]. More generally, how can we control a pathogen using our understanding of ecology and evolution? In particular, what are the roles of competition, cooperation, and phenotypic, genotypic, and spatial heterogeneity? And, how may we leverage them to design optimal treatment protocols?
A further line of research in the lab is understanding mechanisms of selection and evolutionary algorithms. The replicator equation assumes proportional selection: the number of offspring is proportional to the difference between the payoffs a replicator receives and the average payoff all other replicators receive. Under truncation selection, however, replicators with sufficient payoffs survive to reproduce [journal]. Interestingly, the mathematics of this project are related to those of timing in public goods games [journal]. Both models are limits of a more general two-stage process represented by a differential algebraic equation. We are keen to continue this project by understanding the effects and relations between these and related concepts in evolutionary computation more deeply and by developing a more general theory of selection with applications to biology and computer science.
Bryce completed his MSc and PhD in Mathematics at the University of Guelph under the guidance of Chris Bauch, and was a postdoc under Derviş Can Vural at the University of Notre Dame, Erol Akçay at the University of Pennsylvania, and Troy Day and Felicia Magpantay at Queen's University. Starting August 2022, he is an Assistant Professor in the Department of Mathematics at Florida State University.
Ruiyang is a student at Queen's University in Kingston, Ontario, Canada. She has a preprint available: Relational utility and social norms in games [SSRN].
Department of Mathematics
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Florida State University
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