Approaches to complexity engineering
Physica D
Towards a theory of emergent functionality
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Emergence: from chaos to order
Emergence: from chaos to order
Dynamics of complex systems
A new kind of science
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Self-Organization in Biological Systems
Self-Organization in Biological Systems
Selection, tinkering, and emergence in complex networks
Complexity - Special issue: Selection, tinkering, and emergence in complex networks
Organic computing: on the feasibility of controlled emergence
Proceedings of the 2nd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Applying ADELFE Methodology to a Mechanism Design Problem
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Basic Concepts and Taxonomy of Dependable and Secure Computing
IEEE Transactions on Dependable and Secure Computing
Self-organization in multi-agent systems
The Knowledge Engineering Review
Architectural strategy and design evolution in complex engineered systems
Architectural strategy and design evolution in complex engineered systems
A metadata-based architectural model for dynamically resilient systems
Proceedings of the 2007 ACM symposium on Applied computing
Robustness and Dependability of Self-Organizing Systems - A Safety Engineering Perspective
SSS '09 Proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems
MetaSelf: an architecture and a development method for dependable self-* systems
Proceedings of the 2010 ACM Symposium on Applied Computing
Distributed systems – from natural to engineered: three phases of inspiration by nature
International Journal of Bio-Inspired Computation
Emergent engineering: a radical paradigm shift
International Journal of Autonomous and Adaptive Communications Systems
Advances in complexity engineering
International Journal of Bio-Inspired Computation
Emergence versus self-organisation: different concepts but promising when combined
Engineering Self-Organising Systems
About engineering complex systems: multiscale analysis and evolutionary engineering
Engineering Self-Organising Systems
Engineering complex systems: implications for research in systems engineering
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
The theory of social functions: challenges for computational social science and multi-agent learning
Cognitive Systems Research
A method fragments approach to methodologies for engineering self-organizing systems
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Natural Computing: an international journal
Model checking-based safety verification for railway signal safety protocol-I
International Journal of Computer Applications in Technology
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Complexity science has seen increasing interest in the recent years. Many engineers have discovered that traditional methods come to their limits when coping with complex adaptive systems or autonomous agents. To find alternatives, complexity science can be applied to engineering, resulting in a quickly growing field, referred to as complexity engineering. Most current efforts come either from scientists who are interested in bio-inspired methods and working in computer science or mobile robots, or they come from the area of systems engineering. This article reviews the definitions of the most important concepts such as emergence and self-organisation from an engineer's perspective, and analyses different types of nature-inspired technology. This is the first part of a set of two-articles on this topic; the second one provides a survey of currently existing approaches to complexity engineering, identifies challenges and gives directions for further research.