Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
The conscious mind: in search of a fundamental theory
The conscious mind: in search of a fundamental theory
The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
Emergence: from chaos to order
Emergence: from chaos to order
Dynamics of complex systems
Architecture of Systems Problem Solving
Architecture of Systems Problem Solving
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Taxonomy for the modeling and simulation of emergent behavior systems
SpringSim '07 Proceedings of the 2007 spring simulation multiconference - Volume 2
The possibility of a pluralist cognitive science
Journal of Experimental & Theoretical Artificial Intelligence - Pluralism and the Future of Cognitive Science
Minds and Machines
Scaling properties of transcription profiles in gene networks
International Journal of Bioinformatics Research and Applications
Measuring autonomy and emergence via granger causality
Artificial Life
Emergent phenomena only belong to biology
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Neutral emergence and coarse graining
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
ICCSA'06 Proceedings of the 6th international conference on Computational Science and Its Applications - Volume Part I
About engineering complex systems: multiscale analysis and evolutionary engineering
Engineering Self-Organising Systems
Diogenes, a process for identifying unintended consequences
Systems Engineering
Formalization of emergence in multi-agent systems
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
Post-mortem analysis of emergent behavior in complex simulation models
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
On the evolution of agency and implications for comprehensively modeling it
Proceedings of the Emerging M&S Applications in Industry & Academia / Modeling and Humanities Symposium
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We argue conceptually and then demonstrate mathematically that it is possible to define a scientifically meaningful notion of strong emergence. A strong emergent property is a property of the system that cannot be found in the properties of the system's parts or in the interactions between the parts. The possibility of strong emergence follows from an ensemble perspective, which states that physical systems are only meaningful as ensembles rather than individual states. Emergent properties reside in the properties of the ensemble rather than of any individual state. A simple example is the case of a string of bits including a parity bit, i.e. the bits are constrained to have, e.g., an odd number of ON bits. This constraint is a property of the entire system that cannot be identified through any set of observations of the state of any or all subsystems of the system. It is a property that can only be found in observations of the state of the system as a whole. A collective constraint is a property of the system, however, the constraint is caused when the environment interacts with the system to select the allowable states. Although selection in this context does not necessarily correspond to biological evolution, it does suggest that evolutionary processes may lead to such emergent properties. A mathematical characterization of multiscale variety captures the implications of strong emergent properties on all subsystems of the system. Strong emergent properties result in oscillations of multiscale variety with negative values, a distinctive property. Examples of relevant applications in the case of social systems include various allocation, optimization, and functional requirements on the behavior of a system. Strongly emergent properties imply a global to local causality that is conceptually disturbing (but allowed!) in the context of conventional science, and is important to how we think about biological and social systems.