Title :
Symmetric networks foster to evolve desirable turn-taking rules in dispersion games
Author :
Namatame, Akira ; Sato, Hiroshi
Author_Institution :
Comput. Sci. Dept., Nat. Defense Acad., Yokosuka
Abstract :
Using a game-theoretic model combined with the evolutionary model, we investigate the conditions under which the desirable interaction rules will evolve and sustain in various social interaction settings. The direction of the research to come is to understand how the interaction structure, the network topology, determines the path of evolutionary dynamics. For the emergence of desirable outcomes at the macroscopic level, the patterns of social interaction are critical. We find that the efficient and fair outcome emerges relatively quickly in symmetric networks where each agent plays the game with the same number of players. In symmetric networks, agents appear to easily recognize the possibility of a coordinated turn-taking behaviour or alternating reciprocity as a means to generate an efficient and fair outcome.
Keywords :
evolutionary computation; game theory; learning (artificial intelligence); multi-agent systems; topology; EVOLUTIONARY game theory; agent interaction; desirable interaction rule; dispersion game theoretic model; learning algorithm; network topology; social interaction; symmetric network foster; turn-taking rule; Arm; Computer simulation; Game theory; Genetic algorithms; Genetic mutations; Learning; Network topology; Thin film transistors;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4982989