Complex systems and their phenomena are ubiquitous as they can be
found in biology, finance, the humanities, management sciences,
medicine, physics and similar fields.

For many problems in these fields, there are no conventional ways to
mathematically or analytically solve them completely at low cost.

Part I Fuzzy Data Analysis.-

Part II Hybrid Intelligent Systems.-

Part III Uncertainty in Knowledge-based Systems.-

Part IV Intelligent Data Analysis.-

Part V Applications.-

Part VI Closing Remarks.

Complex systems and their phenomena are ubiquitous as they can be
found in biology, finance, the humanities, management sciences,
medicine, physics and similar fields.

For many problems in these fields, there are no conventional ways to
mathematically or analytically solve them completely at low cost. On
the other hand, nature already solved many optimization problems
efficiently. Computational intelligence attempts to mimic
nature-inspired problem-solving strategies and methods.

These strategies can be used to study, model and analyze complex
systems such that it becomes feasible to handle them. Key areas of
computational intelligence are artificial neural networks,
evolutionary computation and fuzzy systems.

As only a few researchers in that field, Rudolf Kruse has contributed
in many important ways to the understanding, modeling and application
of computational intelligence methods. On occasion of his 60th
birthday, a collection of original papers of leading researchers in
the field of computational intelligence has been collected in this
volume.