Near-Minimal Node Control of Networked Evolutionary Games
| Autor: | James Robert Riehl, Ming Cao |
|---|---|
| Přispěvatelé: | Discrete Technology and Production Automation |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | 33rd Benelux Meeting on Systems and Control University of Groningen |
| Popis: | We investigate a problem related to the controllability of networked evolutionary games, first presenting an algorithm that computes a near-minimal set of nodes to drive all nodes in a tree network to a desired strategy, and then briefly discussing an algorithm that works for arbitrary networks using graph partitioning. The study of evolutionary games (EGs) on networks is a topic that has recently become prominent in biology, sociology, economics, physics and a wide range of other disciplines in which dynamic agents interact over networks. Although the primary focus has been to understand the emergence of cooperation and other behaviors for various types of games, dynamics, and network structures, there are many situations throughout the fields mentioned above in which one might want to control the outcome of the game or cause a particular behavior to emerge. Although we are starting to see more literature on evolutionary games from a feedback control perspective [1] [2], to our knowledge there has not yet been an algorithmic method propo |
| Databáze: | OpenAIRE |
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