Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity and dynamical systems theory, several authors have turned to the notion of constraints on state transitions. Drawing on complexity theory directly, this paper builds on those accounts, further developing the constraint-based interpretation of emergence and arguing that such accounts recover many of the features of more traditional accounts. We (...) show that the constraint-based account of emergence also leads naturally into a meaningful definition of self-organization, another concept that has received increasing attention recently. Along the way, we distinguish between order and organization, two concepts which are frequently conflated. Finally, we consider possibilities for future research in the philosophy of complex systems, as well as applications of the distinctions made in this paper. (shrink)

In this paper we suggest a clarification in relation to the notions of computational and intrinsic emergence, by showing how the latter is deeply connected to the new Logical Openness Theory, an original extension of Gödel theorems to the model theory. The epistemological scenario we are going to make use of is that of the theory of vision, a particularly instructive one. In order to reach our goal we introduce a dynamic theory of relationship between the observer and the observed (...) which takes into account the co-adaptive processes as well as the ecological nature of the mind/world relations. In order to fulfill the requirements of complexity sciences, this theory assumes that the scientific activity has to be able to comprehend the adaptive dynamics between system and environment as well as the model and the context where it is applied. This leads to an adaptive epistemology based on logical openness which overcomes the thigh corners of both naïve objectivist conception and radical relativism temptations by stressing that the knowledge building is a process of continuous shifting from the “frozen” syntactical dimensions to the plurality choices which make possible for mind and world to meet each other. (shrink)

As a significant extension of our previous calculus of logical differentials and moving logic, we propose here a mathematical diagram for specifying the emergence of novelty, through the construction of some “differentials” related to cohomological computations. Later we intend to examine how to use these “differentials” in the analysis of anticipation or evolution schemes. This proposal is given as a consequence of our comments on the Ehresmann–Vanbremeersch’s work on memory evolutive systems, from the two points of view which are characterization (...) of life and use of categorical modeling. It would not be possible to conceive of the “differentials” outside the frame of a MES. Furthermore, we hope that this diagram will be useful to exhibit the “emergence of sense” in discourses, and this idea is supported here by a brief examination of how a discourse could be seen as a living system. (shrink)

We consider processes of emergence within the conceptual framework of the Information Loss principle and the concepts of systems conserving information; systems compressing information; and systems amplifying information. We deal with the supposed incompatibility between emergence and computability tout-court. We distinguish between computational emergence, when computation acquires properties, and emergent computation, when computation emerges as a property. The focus is on emergence processes occurring within computational processes. Violations of Turing-computability such as non-explicitness and incompleteness are intended to represent partially the (...) properties of phenomenological emergence, such as logical openness, given by the observer’s cognitive role; structural dynamics where change regards rules rather than only values; and multi-modelling where multiple non-equivalent models are required to model such structural dynamics. In this way, we validate, from an epistemological viewpoint, models and simulations of phenomenological emergence where the sequence of events constitutes the natural, analogical non-Turing computation which a cognitive complex system can reproduce through learning. Reproducibility through learning is different from Turing-like computational iteration. This paper aims to open a new, non-reductionist understanding of the conceptual relationship between emergence and computability. (shrink)

I argue that much of current concern with the role of causality and strong emergence in natural processes is based upon an unreasonable expectation placed on our ability to formalize scientific knowledge. In most disciplines our formalization ability is an expectation rather than a scientific result. This calls for an empirical approach to the study of causation and emergence. Finally, I suggest that for advances in complexity research to occur, attention needs to be paid to understanding what role computation plays (...) in this experimental approach. (shrink)

I argue that much of current concern with the role of causality and strong emergence in natural processes is based upon an unreasonable expectation placed on our ability to formalize scientific knowledge. In most disciplines our formalization ability is an expectation rather than a scientific result. This calls for an empirical approach to the study of causation and emergence. Finally, I suggest that for advances in complexity research to occur, attention needs to be paid to understanding what role computation plays (...) in this experimental approach. (shrink)

This article reviews the seven “visions” of evolution proposed by Depew and Weber , concluding that each posited relationship between natural selection and self-organization has suited different aims and approaches. In the second section of the article, we show that these seven viewpoints may be collapsed into three fundamentally different ones: natural selection drives evolution; self-organization drives evolution; and natural selection and self-organization are complementary aspects of the evolutionary process. We then argue that these three approaches are not mutually exclusive, (...) since each may apply to different stages of development of different systems. What emerges from our discussion is a more encompassing view: that self-organization proposes what natural selection disposes. (shrink)

Emergent properties (EPs) are not causally reducible to the properties of a complex system’s elements. If a system’s properties cannot be reduced to those of any of its components, then that system is effectively a singular entity (SE). EPs are thus not properties of known complexes, but of SEs. A precise description of the parameters necessary to observe a physical system as an SE is thus necessary to establish under what conditions properties are understood as emergent. That description is provided (...) in terms of the temporal dynamics of systems and their internal/external interactions. (shrink)