Rocking stumper and jumping snakes from a dynamical systems approach to artificial life

Dynamical systems offer intriguing possibilities as a substrate for the generation of behaviour due to their rich behavioural complexity. However this complexity together with the largely covert relation between the parameters and the behaviour of the agent is also the main hindrance in the goal oriented design of a behaviour system. The paper presents a general approach to the self-regulation of dynamical systems so that the design problem is circumvented. We consider the controller (a neural network) as the mediator for changes in the sensor values over time and define a dynamics for the parameters of the controller by maximising the dynamical complexity of the sensorimotor loop under the condition that the consequences of the actions taken are still predictable. This very general principle is given a concrete mathematical formulation and implemented in an extremely robust and versatile algorithm for the parameter dynamics of the controller. We consider two different applications, a mechanical device called the rocking stumper and the ODE simulations of a ”snake” with five degrees of freedom. From this and many other applications we conclude that our self-regulating parameter dynamics engenders artificial life forms of unknown so far dynamical complexity.