Complexity

Overview

Aims and Scope

Effective with the 2011 volume, this journal will be published in an online-only format.

Complexity is a bi-monthly, cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like "chaos," "self-organization," and "emergence" that are often used in completely different ways in science and in daily life.

Readership

Mathematicians · physicists · computer scientists · biologists · engineers · economists · social scientists

Keywords

complex adaptive systems, chaos research, neural networks, evolutionary game theory, genetic algorithms, time series analysis, symbolic dynamics, fractals, robustness, quantum computing, population dynamics, collective behavior, journal, online journal, Wiley Online Library

Abstracting and Indexing Information

• BIOBASE: Current Awareness in Biological Sciences (Elsevier)
• Biological Abstracts (Thomson Reuters)
• BIOSIS Previews (Thomson Reuters)
• CompuMath Citation Index (Thomson Reuters)
• CompuScience Database (FIZ Karlsruhe)
• Computer & Communications Security Abstracts (Emerald)
• Computer & Information Systems Abstracts (ProQuest)
• Computer Abstracts (Emerald)
• Computer Science Index (EBSCO Publishing)
• Computing Reviews (ACM)
• Current Index to Statistics (ASA/IMS)
• INSPEC (IET)
• Journal Citation Reports/Science Edition (Thomson Reuters)
• Mathematical Reviews/MathSciNet/Current Mathematical Publications (AMS)
• PSYNDEX (ZPID)
• Science Citation Index Expanded (Thomson Reuters)
• SCOPUS (Elsevier)
• Web of Science (Thomson Reuters)