Population Games with Sub-Strategies and Evolutionary Nash Equilibrium Learning
Abstract
Abstract We establish a modified notion of Nash equilibrium learning—convergence of the population state to the Nash equilibria set—in a generalization of the standard population games and evolutionary dynamics framework using system-theoretic passivity methods. In this setting, we allow each strategy to involve a sequence of sub-tasks that must be completed before strategy revision so long as the durations of the sub-tasks can be modeled with Erlang or exponential distributions. Furthermore, several canonical classes of natural learning rules are established and useful properties are derived.
Fields of Study & Subjects
Game Theory and Applications
Evolutionary Game Theory and Cooperation
Reinforcement Learning in Robotics
Publication details
- Journal / source
- Dynamic Games and Applications
- Publisher
- Springer Science and Business Media LLC
- Volume
- 16
- Issue
- 1
- Pages
- 426–452
- Publication date
- 17 February 2026
- Language
- EN