Search Talks

This lecture examines the long-term behaviour of MEGs, focusing on fixation probabilities, fixation times, and stochastic slowdowns. It explores key questions such as if, when, and how a strategy persists in the long run. The transition from static equilibrium analysis to dynamic evolution is discussed, incorporating concepts like mutation-selection equilibrium, the 1/3 rule, risk dominance, and their generalisations to multiplayer settings. Additionally, the role of multiplayer games in mutualism is highlighted, showing how cooperative interactions persist over time in an ecological framework.

This talk will introduce the Bala-Goyal model of epistemic networks, where agents on a network learn to solve a decision problem by performing actions and sharing the results of those actions with their neighbors.  We will discuss the conditions under which agents on these networks successfully learn to perform optimal outcomes, and how network structure can influence time to convergence and accuracy.

Many theorists have employed game theory to model the emergence of stable social norms, or natural “social contracts.” One branch of this literature uses bargaining games to show why many societies have norms and rules for fairness. In cultural evolutionary models, fair bargaining emerges endogenously because it is an efficient way to divide resources. But these models miss an important element of real human societies – divisions into groups or social categories. Once such groups are added to cultural evolutionary models, fairness is no longer the expected outcome.  Instead “discriminatory norms” often emerge where one group systematically gets more when dividing resources. I show why the addition of categories to bargaining models leads to unfairness, and discuss the role of power us in this process. I also address how categories might emerge to support inequity, and the possibility of modeling social change. Altogether this work emphasizes that if one wishes to understand the naturalistic emergence of social contracts, one must account for the presence of categorical divisions, and unfairness, as well as for norms of fairness.

Bacteriophages are the most abundant organisms on the planet and play key roles as shapers of ecosystems and drivers of bacterial evolution. Temperate phages can choose between (i) lysis: exploiting their bacterial hosts to produce multiple offspring phage and releasing them by lysing the host cell, and (ii) lysogeny: establishing a mutually beneficial relationship with the host by integrating their chromosome into the host cell’s genome. I will describe how we combine dynamical systems and game theory to model the  competition of phage mutants that have different lysogeny propensities. We find that there is a narrow range of optimal propensity values that phages can evolve, and this predicted range covers the values observed for various phage species. Our results also offer an explanation for why temperate phages tend to utilize bistable switches that can incorporate the number of infecting phage into the lysis-lysogeny decision. If there is time, I will describe other work that examines the range of network structures that can produce such functionality.

Multiplayer Evolutionary Games (MEGs) extend classical evolutionary game theory by incorporating interactions among multiple participants rather than just two. This lecture introduces MEGs and their foundational connection to population genetics and their evolutionary dynamics. Theoretical principles such as fitness, selection, and mutation are explored, illustrating how MEGs capture non-linear interaction effects. The importance of higher-order interactions is emphasized, demonstrating how MEGs naturally extend traditional evolutionary models to more complex, real-world scenarios.

In a series of four lectures, I give an introduction to evolutionary game theory and the literature on the evolution of cooperation. This series covers
(i) Evolutionary game theory in infinite and finite populations (Replicator dynamics, Moran process);
(ii) Evolution of cooperation and direct reciprocity
(iii) Social norms and the evolution of indirect reciprocity
(iv) Some current research directions (e.g., direct reciprocity in complex environments).

We present a model of opinion formation game resource limited utility-maximizing agents interacting over a social network. The opinion dynamics is the result of each agent simultaneously revising its opinion by gradient ascent of its utility function. We analyze the evolution of opinions, including boundedness of opinions, convergence to an equilibrium and oscillatory behavior. In some special cases, we comment on the relative dominance of the agents on the steady state opinions. We also establish connections to Nash equilibria and prices of anarchy.

Bio: Pavan Tallapragada is an Associate Prof. in the Robert Bosch Centre for Cyber Physical Systems at the Indian Institute of Science. His research interests are broadly in multi-agent systems and control, including in multi-robot control, multi-agent reinforcement learning and dynamics of social systems.

Animals in the natural world face many choices, and their decisions with respect to food and habitat have major consequences for their fitness. Many factors influence these behavioural decisions, including the ecological and life history context of individuals. I will present our work analysing how females of a cosmopolitan and generalist pest — the red flour beetle Tribolium castaneum — choose where and how to lay eggs. When presented with a choice of an optimal (wheat flour) vs. a non-optimal resource (finger millet), females sometimes allocate more eggs in finger millet. However, we find that this preference depends on their age and density context, and is tuned to optimize distinct fitness components for their offspring, likely mediated via differential nutrient provisioning. During laboratory evolution in wheat-finger millet habitats, the founder female context also determines evolutionary changes in decision-making, though these maternal effects decline over time. Importantly, founder context also influenced population size and the effect of an inadvertent parasitic infection in our experiment. Our work highlights the role of ecological context in driving female decision-making, and demonstrates some wide-ranging effects of founder context on adaptation and trait evolution.

Beginning with the intimate relationship between recursive algorithms and dynamical systems, I shall describe some common dynamics that serve as templates for `stateless' learning. This will be followed by reinforcement learning for dynamic systems, using Markov decision processes as a test case.

In a series of four lectures, I give an introduction to evolutionary game theory and the literature on the evolution of cooperation. This series covers
(i) Evolutionary game theory in infinite and finite populations (Replicator dynamics, Moran process);
(ii) Evolution of cooperation and direct reciprocity
(iii) Social norms and the evolution of indirect reciprocity
(iv) Some current research directions (e.g., direct reciprocity in complex environments).