  Autonomous space vehicles need adaptive control strategies that can
accommodate unanticipated environmental conditions. The evaluation of new
strategies can often be done only by actually trying them out in the real
physical environment. Consequently, a candidate control strategy must be deemed
safe--i.e., it won't damage any systems--prior to being tested online. How to
do this efficiently has been a challenging problem.
  We propose using evolutionary programming in conjunction with a formal
verification technique (called model checking) to evolve candidate control
strategies that are guaranteed to be safe for implementation and evaluation.
