Recently in the fields of artificial life and robotics, several researchers have attempted to let the populations of artificial organisms or real robots synthesize some intra- or inter-species cooperative relationships. Here taking the symbiont-finding problem as such a problem domain, we show how multiple populations of Q-learning artificial organisms synthesize symbiotic behavior needed to achieve their goals effectively. Optimality of thus synthesized behavior and its organization processes are also analyzed.