Cleotilde Gonzalez, Ph.D. (CMU)
Dietrich College of Humanities and Social Sciences
Carnegie Mellon University
How Group Learning Unfolds from Individuals: Interdependence, Aggregation, and Strategy
Historically, group behavior (networks, organizations) has been studied as an aggregate effect, where the unit of learning is the group rather than the individual, and learning phenomena observed at the group level (e.g., exploration/exploitation, similarity effects) often resembles what is known from individual learning. We argue that all learning takes place inside individual human heads, and that group behavior emerges from individual strategies, the interdependence among individuals in a group, and the aggregation behavior of individuals in a group. In this talk I will discuss our efforts to demonstrate this premise. I will highlight results derived from experiments in 2-person games and the role of information regarding their interdependence on the individual and group behavior. I will also demonstrate how a cognitive model of individual learning based on Instance-Based Learning (IBL) Theory was expanded to account for group learning. Using IBL models, I will demonstrate effects of a taxonomy of payoff interdependence in 2-person interactions, and escalate those results to groups of various structures (e.g. fully connected, lattice networks). We find that mutually rewarding actions between members of a group emerge from individual selfishness when the payoff interdependence is conducive to mutually beneficial actions. We also find that the more connections there are in a group (e.g., fully connected network) the less likely it is that individuals will learn mutually rewarding actions.
Cleotilde (Coty) Gonzalez is a Research Professor of Decision Sciences in the Department of Social and Decision Sciences and the Founding Director of the Dynamic Decision Making Laboratory (DDMLab) at Carnegie Mellon University. She is also affiliated to the Security and Privacy Institute (CyLab), the Center for Behavioral Decision Research (CBDR) and other research centers at Carnegie Mellon University. Her work focuses on the experimental studies and computational representations of the cognitive processes involved in decisions from experience in dynamic environments.
She is a Fellow of the Human Factors and Ergonomics Society and member of the Governing Board of the Cognitive Science Society. She is part of Editorial Boards of various prestigious journals including: Cognitive Science Journal, Decision, the Journal of Experimental Psychology-General, the Journal of Behavioral Decision Making, the Human Factors Journal, and the System Dynamics Review. Coty has published hundreds of papers in journals and peer-reviewed proceedings involving a diverse set of fields deriving from her contributions to Cognitive Science. Her work includes the development of a theory of decisions from experience called Instance-Based Learning Theory (IBLT), from which many computational models have emerged in areas as diverse as: cybersecurity, network science, human-machine teaming, and others. She has been Principal or Co-Investigator on a wide range of multi-million and multi-year collaborative efforts with government and industry, including current efforts on Collaborative Research Alliances; Multi-University Research Initiative grants from the Army Research Laboratories and Army Research Office; and large collaborative projects with the Defense Advanced Research Projects Agency (DARPA).