Ryan Carr, Eric Raboin, Austin Parker, Dana Nau
This paper examines the value of innovation within a culture by looking at "innovate" moves in the Cultaptation Project's social learning game (Boyd et al. 2008). We produce a mathematical model of a simplified version of this game, and produce analytic methods for determining optimal innovation behavior in this game. In particular, we provide a formula for determining when one should stop innovating and start exploiting one's accumulated knowledge. We create an agent for playing the social learning game based on these results, and in our experiments, the agent exhibited near-optimal behavior.
Subjects: 7.1 Multi-Agent Systems; 1.8 Game Playing
Submitted: Jun 22, 2008