Online research in philosophy

In this paper we intend to examine whether there are examples for emergence to be found in physics. The answer depends on the concept of emergence one invokes. We distinguish two such concepts, those of Broad and Kim. We will argue that it is unlikely that there will be examples with respect to the former because it runs counter to an explanatory strategy that is both well entrenched in physical practice and to a certain degree flexible. On the other hand we will argue that all those physical systems that provide an example for supervenience are at the same time examples for emergence - at least if one defines emergence the way Kim does.

This paper tries to get a grip on two seemingly conflicting intuitions about reductionism in quantum mechanics. On the one hand it is received wisdom that quantum mechanics puts an end to ‘reductionism’. Quantum-entanglement is responsible for such features of quantum mechanics as holism, the failure of supervenience and emergence. While I agree with these claims I will argue that it is only part of the story. Quantum mechanics provides us with thorough-going reductionist explanations. I will distinguish two kinds of micro-explanation (or micro-‘reduction’). I will argue that even though quantum-entanglement provides an example for the failure of one kind of micro-explanation it does not affect the other. Contrary to a recent paper by Kronz and Tiehen I claim that the explanation of the dynamics of quantum mechanical systems is just as reductionist as it used to be in classical mechanics.

Examination of attempts at theory reduction (S to T) shows that a process of cognitive emergence is involved in which concepts of S, Cs, emerge from T. This permits the 'bridge laws' to be stated. These are not in conflict with incommensurability of the Cs with the CT. Cognitive emergence may occur asymptotically or because of similarities of mathematical expressions; it is not necessarily holistic. Mereologically and nonmereologically related theory pairs are considered. Examples are chosen from physics. An important distinction is made between 'theory reduction' and 'reductive explanation'.

Weak emergence is the view that a system’s macro properties can be explained by its micro properties but only in an especially complicated way. This paper explains a version of weak emergence based on the notion of explanatory incompressibility and “crawling the causal web.” Then it examines three reasons why weak emergence might be thought to be just in the mind. The first reason is based on contrasting mere epistemological emergence with a form of ontological emergence that involves irreducible downward causation. The second reason is based on the idea that attributions of emergence are always a reflection of our ignorance of non-emergent explanations. The third reason is based on the charge that complex explanations are anthropocentric. Rather than being just in the mind, weak emergence is seen to involve a distinctive kind of complex, macro-pattern in the mind-independent objective micro-causal structure that exists in nature. The paper ends by addressing two further questions. One concerns whether weak emergence applies only or mainly to computer simulations and computational systems. The other concerns the respect in which weak emergence is dynamic rather than static.

The concept of weak emergence is a refinement or specification of the intuitive, general notion of emergence. Basically, a fact about a system is said to be weakly emergent if its holding both (i) is derivable from the fundamental laws of the system together with some set of basic (non-emergent) facts about it, and yet (ii) is only derivable in a particular manner, called “simulation.” This essay analyzes the application of this notion Conway’s Game of Life, and concludes that a modification of the notion would provide a better refinement of the general notion of emergence. It is proposed that emergence be taken as a matter of degree, defined in terms of the amount of simulation required to derive a fact.

First, a principal distinction between two different kinds of semiotic investigations is introduced, both required in the study of living signs and signs of life. Then, the attempt within the new field of Artificial Life to model and synthesise computationally based living systems is discussed with special attention paid to the possible emergence of genuine life-like behaviour in such models of for instance self-reproduction. Remarks will be made on a seemingly odd aspect of the biological concept of life; that it is not as coherent as normally conceived of. In general, biosemiotic emergence of new sign functions is distinguished from other kinds of emergence that pertain to the domain of the observer and the modeling relation.

Weak emergence has been offered as an explication of the ubiquitous notion of emergence used in complexity science (Bedau 1997). After outlining the problem of emergence and comparing weak emergence with the two other main objectivist approaches to emergence, this paper explains a version of weak emergence and illustrates it with cellular automata. Then it explains the sort of downward causation and explanatory autonomy involved in weak emergence.

Contemporary scientific theories assume a primarily micro-deterministic view of nature. This paper explores the question of whether micro-determinism is incompatible with the alleged emergence of properties and laws that some biologists and philosophers assert occurs in various biological systems. I argue that a preferable unified treatment of these emergence claims takes properties, rather than laws, to be the units of emergence. Four distinct conceptions of emergence are explored and three shown to be compatible with micro-determinism. The remaining concept of emergence, direct macro-determination, does not, I argue, meet the general requirement that an adequate scientific explanation provide a coherent mechanism or effective means of determination.

I investigate the relationship between adaptation, as defined in evolutionary theory through natural selection, and the concept of emergence. I argue that there is an essential correlation between the former, and “emergence” defined in the field of algorithmic simulations. I first show that the computational concept of emergence (in terms of incompressible simulation) can be correlated with a causal criterion of emergence (in terms of the specificity of the explanation of global patterns). On this ground, I argue that emergence in general involves some sort of selective processes. Finally, I show that a second criterion, concerning novel explanatory regularities following the emergence of a pattern, captures the robustness of emergence displayed by some cases of emergence (according to the first criterion). Emergent processes fulfilling both criteria are therefore exemplified in evolutionary biology by some so-called “innovations”, and mostly by the new units of fitness or new kinds of adaptations (like sexual reproduction, multicellular organisms, cells, societies) sometimes called “major transitions in evolution”, that recent research programs (Maynard-Smith and Szathmary 1995 ; Michod 1999 ) aims at explaining.

Emergence is a universal phenomenon that can be defined mathematically in a very general way. This is useful for the study of scientifically legitimate explanations of complex systems, here defined as hyperstructures. A requirement is that the observation mechanisms are considered within the general framework. Two notions of emergence are defined, and specific examples of these are discussed.