Abstract
Recently, robots are requested to operate in a complex and difficult to predict variable environment like living space.
For this request, many researchers study in the field of individual intelligence or multi agents.But there are not many researchers about growth of individual intelligence of robot.In this paper,we will target improvement of individual learning.To realize this, we propose a mechanism which agents exchange information on the crowd about learning method as combination of action selection method and action evaluation method on reinforcement learning and learn learning method adapting to each situations.We apply proposed system to n-armed bandit problem and show a validity with computer simulation.
