Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

SOE: Fachverband Physik sozio-ökonomischer Systeme

SOE 3: Economic Models and Evolutionary Game Theory I

SOE 3.5: Vortrag

Montag, 26. März 2012, 12:00–12:15, H 0110

Complex dynamics in game learning — •James Sanders¹, Tobias Galla¹, and J. Doyne Farmer² — ¹School of Physics and Astronomy, The University of Manchester, Manchester, UK — ²Santa Fe Institute, Santa Fe, New Mexico, USA

Game learning processes are of interest in many fields, from the study of financial markets in which traders learn from their past successes and failures, to the design of computer systems that can improve their behaviour based on previous experiences. We study experience-weighted attraction, an empirically-based model of game learning behaviour, focusing in particular on the conditions under which it displays chaotic dynamics. We discuss low-dimensional games as well as those with a large number of strategies, where very high-dimensional chaotic attractors can be seen. This has potential implications for complex systems that can be modelled using experience-weighted attraction, as the presence of this kind of complex dynamics places severe limits on the predictability of a system.