Eric Raboin, Ryan Carr, 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. 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 an efficient algorithm for determining how to balance innovation with the need to exploit one's accumulated knowledge. We create an agent for playing the social learning game based on these results.
Submitted: Sep 12, 2008