This book addresses the problems of modeling prediction classification data understanding
and processing in non-stationary and unpredictable environments. It presents major and
well-known methods and approaches for the design of systems able to learn and to fully adapt
its structure and to adjust its parameters according to the changes in their environments. Also
presents the problem of learning in non-stationary environments its interests its
applications and challenges and studies the complementarities and the links between the
different methods and techniques of learning in evolving and non-stationary environments.
