Adaptive Behavior in Continuous Time
MetadataShow full item record
This research investigates population-level behavioral dynamics, how they affect the emergence of self-enforcing conventions, and how they can aid in the design of mechanisms to better achieve policy goals. It seeks to identify why long-run behavior approaches equilibrium in some environments, and fails to do so in others. This question is important because equilibrium is frequently employed to make policy recommendations, so it is necessary to identify when it provides reliable predictions. Further, many strategic environments only reach equilibrium in the long run, so modeling the short run process from which long run equilibria eventually emerge can help answer important policy-relevant questions. To answer these questions this research experimentally investigates behavioral dynamics in continuous-time strategic environments. We find that adaptive models provide remarkably powerful tools for identifying which strategic environments exhibit convergence to equilibrium and for characterizing disequilibrium dynamics in non-convergent strategic environments.
Stephenson, Daniel Graydon (2017). Adaptive Behavior in Continuous Time. Doctoral dissertation, Texas A & M University. Available electronically from