Lecturer: Theodore Pavlic
Fields: Behavioral Ecology, Game Theory, Modeling, Natural History, Collective Behavior, Ants, Bees, Wasps, Social Insects, Social Behavior
Content
In this 4-part course, we delve into the fascinating world of social systems, drawing parallels between the intricacies of social-insect colonies and the complexities of human societies. Through the lens of resilience, robustness, and responsibility, we explore the dual nature of collective behavior, examining how it can both empower and challenge the adaptability of societies.
We begin by unraveling the mechanisms that enable social-insect colonies (with a particular focus on ants and social bees) to flexibly respond to environmental changes, while also scrutinizing the vulnerabilities that arise from individuals valuing public information too much over private information. We will also show motivational examples of natural collective decision-making systems in ant colonies that have qualitatively different cognitive capabilities at the level of the collective than the individual, effectively reducing the burden of individual responsibility in a functioning society.
We then continue to highlight strengths, weaknesses, opportunities, and threats in social systems by reviewing fundamental results from game theory. We start with a review of the Prisoner\’s Dilemma and ask whether it has much practical value. We then transition to a wider range of social games, such as the Hawk–Dove and the Stag Hunt, that highlight how living in societies is challenged not only by alignment of agendas but also coordination of collective action when there is limited information. This sets us up to talk about N-person games and equilibrium concepts that apply to larger social groups, with examples from social foraging to make this more concrete. Empowered with these game-theoretic fundamentals, we can then discuss the problem of altruism in societies and pivot to discussing alternative explanations for altruism based less on social relatedness (responsibility) and more on risk management (resilience and robustness).
In an attempt to close on an optimistic note, we conclude this course with examples of the various benefits of highly integrated social life viewed through the lenses of resilience, robustness, and responsibility. We uncover profound benefits of colony life in many social insects and discuss the mechanisms that underly these adaptations.
Ultimately, this course provides an opportunity to navigate through the complexities of social organization, shedding light on the fundamental principles that underpin the resilience, robustness, and responsibility of societies across the biological spectrum to highlight both how societies can protect from disturbances from the outside while also introducing new risks to manage that come from within.
Literature
- Goss, S., Beckers, R., Deneubourg, J. L., Aron, S., & Pasteels, J. M. (1990). How trail laying and trail following can solve foraging problems for ant colonies. In Behavioural mechanisms of food selection (pp. 661-678). Springer Berlin Heidelberg.
- Dussutour, A., Beekman, M., Nicolis, S. C., & Meyer, B. (2009). Noise improves collective decision-making by ants in dynamic environments. Proceedings of the Royal Society B: Biological Sciences, 276(1677), 4353-4361.
- Weinstein, S., Pavlic, T. P., Walker, S. I., Davies, P. C. W., & Ellis, G. F. R. (2017). Noise and function. In From Matter to Life: Information and Causality (pp. 174-198). Cambridge University Press.
- Pavlic, T. P., & Pratt, S. C. (2013). Superorganismic behavior via human computation. Handbook of human computation, 911-960.
- Wilson, E. O. (1962). Chemical communication among workers of the fire ant Solenopsis saevissima (Fr. Smith) 2. An information analysis of the odour trail. Animal Behaviour, 10(1-2), 148-158.
- Guo, X., Lin, M. R., Azizi, A., Saldyt, L. P., Kang, Y., Pavlic, T. P., & Fewell, J. H. (2022). Decoding alarm signal propagation of seed-harvester ants using automated movement tracking and supervised machine learning. Proceedings of the Royal Society B, 289(1967), 20212176.
- Sasaki, T., & Pratt, S. C. (2011). Emergence of group rationality from irrational individuals. Behavioral Ecology, 22(2), 276-281.
- Sasaki, T., & Pratt, S. C. (2012). Groups have a larger cognitive capacity than individuals. Current Biology, 22(19), R827-R829.
- Burns, D. D., Franks, D. W., Parr, C., & Robinson, E. J. (2021). Ant colony nest networks adapt to resource disruption. Journal of Animal Ecology, 90(1), 143-152.
- Wenzel, J. W., & Pickering, J. (1991). Cooperative foraging, productivity, and the central limit theorem. Proceedings of the National Academy of Sciences, 88(1), 36-38.
- Sendova-Franks, A. B., & Franks, N. R. (1994). Social resilience in individual worker ants and its role in division of labour. Proceedings of the Royal Society of London. Series B: Biological Sciences, 256(1347), 305-309.
- Middleton, E. J., & Latty, T. (2016). Resilience in social insect infrastructure systems. Journal of The Royal Society Interface, 13(116), 20151022.
- Linksvayer, T. A., & Janssen, M. A. (2009). Traits underlying the capacity of ant colonies to adapt to disturbance and stress regimes. Systems Research and Behavioral Science: The Official Journal of the International Federation for Systems Research, 26(3), 315-329.
- Naug, D. (2009). Structure and resilience of the social network in an insect colony as a function of colony size. Behavioral Ecology and Sociobiology, 63, 1023-1028.
- Naug, D. (2008). Structure of the social network and its influence on transmission dynamics in a honeybee colony. Behavioral Ecology and Sociobiology, 62, 1719-1725.
- Stroeymeyt N, Casillas-Pérez B, Cremer S. Organisational immunity in social insects. Current Opinion in Insect Science. 2014 Nov 1;5:1-5.
Lecturer
Dr. Theodore (Ted) Pavlic [@TedPavlic] is an Associate Professor at Arizona State University (ASU) jointly appointed in the School of Computing and Augmented Intelligence and the School of Life Sciences. His industry experience (before graduate school) includes work in analog electronics for instrumentation as well as a decade working in software engineering. In 2010, he received his PhD from The Ohio State University in electrical and computer engineering where he studied the design of nonlinear and optimal control systems for autonomy that were inspired by models of animal decision making from behavioral ecology. He followed his PhD with postdoctoral training in both computer science (software verification techniques applied to cyber-physical systems) and animal behavior (collective behavior of ants) and then started his faculty position at ASU in 2015. His research focuses on understanding adaptive decision-making strategies in autonomous systems. To this end, his laboratory does empirical work with natural systems, such as understanding resource allocation and decision-making in social-insect colonies, and does engineering work building decision-making algorithms for artificial systems, such as decentralized energy management systems for the built environment and novel neural network architectures inspired by the insect brain. Just as the biological models provide inspiration for novel engineering solutions, the engineering problems inspire new lines of scientific inquiry about those biological systems. Students and postdoctoral researchers in Pavlic\’s lab come from a wide range of disciplines, from Computer Science/Engineering to Industrial Engineering to Applied Mathematics to Biology and Animal Behavior, and participate in a similarly diverse range of academic communities. Professor Pavlic was the founding associate director of research for The Biomimicry Center at Arizona State University and continues to be closely associated with the center. He is also active in several of the efforts across ASU\’s campus focused on complex adaptive systems science. He is a member of several professional societies across engineering and the sciences, including IEEE, ACM, ABS, and IUSSI.
Affiliation: Arizona State University
Homepage: https://search.asu.edu/profile/1995237