  There is a belief that complexity and chaos are essential for adaptability.
But life deals with complexity every moment, without the chaos that engineers
fear so, by invoking goal-directed behaviour. Goals can be programmed. That is
why living organisms give us hope to achieve adaptability in robots. In this
paper a method for the description of a goal-directed, or programmed,
behaviour, interacting with uncertainty of environment, is described. We
suggest reducing the structural (goals, intentions) and stochastic components
(probability to realise the goal) of individual behaviour to random variables
with nominal values to apply probabilistic approach. This allowed us to use a
Normalized Entropy Index to detect the system state by estimating the
contribution of each agent to the group behaviour. The number of possible group
states is 27. We argue that adaptation has a limited number of possible paths
between these 27 states. Paths and states can be programmed so that after
adjustment to any particular case of task and conditions, adaptability will
never involve chaos. We suggest the application of the model to operation of
robots or other devices in remote and/or dangerous places.
