Sigrunn Eliassen (University of Bergen, Norway)
Biography
Eliassen’s research primarily focuses on the evolution of mating systems and cooperative behaviors. Using evolutionary modeling, she examines how mating strategies alter the incentives for males and females to invest in parental care and cooperation. Her work often bridges the gap between ecological modeling and evolutionary biology, providing insights into how animals adapt their behaviors in response to environmental conditions.
She is also deeply interested in how animals use information and learn. Alongside her colleagues, she has explored mechanisms of decision-making and developed a new framework for behavioral modeling. Her contributions to the field of behavioral ecology include publications exploring topics such as extra-pair mating, decision-making in animals, and the adaptive value of learning in foraging behavior.
In addition to her research, Eliassen is actively involved in enhancing teaching practices and student learning in higher education. She has co-authored several academic articles that investigate the impact of autonomy and motivation on student learning and academic performance.
Adaptive Decision-Making and Animal Interactions in Social Networks
Classical game theory has trained our intuition about important aspects of social interactions, from conflict to cooperation. Moving beyond basic models, we recognize that interactions are dynamic, with costs and benefits inherently linked to local contexts. Animal responses are influenced by previous experiences and adaptive decision-making. The ability to acquire, integrate, and restrict information can alter individual strategies and influence evolutionary dynamics.
In this talk, I will illustrate these concepts using a model of coevolving mating strategies in social networks. Additionally, I will propose a framework for adaptive decision-making that considers the cognitive mechanisms enabling animals to behave autonomously, make predictions about the future, and make adaptive decisions in real time. Viewing animals as agents with goal-directed, rather than purely stimulus-driven, cognitive and behavioral control may enhance our understanding of animal decision-making in natural environments.
