A parsimonious model for locomotor in virtual agents based on dynamical coupling with the environment

In the domain of virtual agents modeling, computationalist approaches tend to predominate. The lack of plausibility of the rules in nature provides models with a low capacity to generalize and a very limited insight into behavioral phenomena. An alternative view is that behavior could emerge as a whole from the basic principles of non-linear dynamics that underlie such behavior in the environment. This paper presents a dynamic agent endowed with a sensing device, a controller and actuators to interact with the environment. The control architecture is based on ordinary differential equations with the function of modulating the stimulus signals to action signals under a sensory-motor flow. The parameter values are defined in an evolutionary process depending on the task to be performed. A series of experiments are presented to illustrate certain qualities of our model such as the adaptability to change, a highly intuitive and flexible design methodology, and a high degree of individual autonomy, among others. We think this kind of modeling is useful in the animation world for modeling flocks, crowds, and swarms as a valid alternative to other less parsimonious techniques.