This paper focuses on the simulation of behavior for autonomous entities in virtual environments. The behavior of these entities must determine their responses not only to external stimuli, but also with regard to internal states. We propose to describe such behavior using fuzzy cognitive maps (FCMs), whereby these internal states might be explicitly represented. This paper presents the use of FCMs as a tool to specify and control the behavior of individual agents. First, we describe how FCMs can be used to model behavior. We then present a learning algorithm allowing the adaptation of FCMs through observation. Copyright © 2010 John Wiley & Sons, Ltd.