This chapter explores some fundamental consequences of the correspondence between physical process and computations. Most physical questions may be answerable only through irreducible amounts of computation. Those that concern idealized limits of infinite time, volume, or numerical precision can require arbitrarily long computations, and so be considered formally undecidable. The behavior of a physical system may always be calculated by simulating explicitly each step in its evolution. Much of theoretical physics has, however, been concerned with devising shorter methods of calculation (...) that reproduce the outcome without tracing each step. Computational irreducibility is common among the systems investigated in mathematics and computation theory, but it may well be the exception rather than the rule, since most physical questions may be answerable only through irreducible amounts of computation. (shrink)

Most philosophical accounts of emergence are incompatible with reduction. Most scientists regard a system property as emergent relative to properties of the system's parts if it depends upon their mode of organization--a view consistent with reduction. Emergence can be analyzed as a failure of aggregativity--a state in which "the whole is nothing more than the sum of its parts." Aggregativity requires four conditions, giving tools for analyzing modes of organization. Differently met for different decompositions of the system, and in different (...) degrees, these conditions provide powerful evaluation criteria for choosing decompositions, and heuristics for detecting biases of vulgar reductionisms. This analysis of emergence is compatible with reduction. (shrink)

Non-reductive physicalists have made a number of attempts to provide the relation of supervenience between levels of properties with enough bite to analyze interesting cases without at the same time losing the relation's acceptability for the physicalist. I criticize some of these proposals and suggest an alternative supplementation of the supervenience relation by imposing a requirement of robustness which is motivated by the notion of structural stability familiar from dynamical systems theory. Robust supervenience, I argue, captures what the non-reductive physicalist (...) wants from supervenience; most importantly, it provides a natural background for reconstructing the notion of (diachronic) property emergence in a way acceptable to physicalists. (shrink)

This paper explicates two notions of emergencewhich are based on two ways of distinguishinglevels of properties for dynamical systems.Once the levels are defined, the strategies ofcharacterizing the relation of higher level to lower levelproperties as diachronic and synchronic emergenceare the same. In each case, the higher level properties aresaid to be emergent if they are novel or irreducible with respect to the lower level properties. Novelty andirreducibility are given precise meanings in terms of the effectsthat the change of a bifurcation (...) or perturbation parameterin the system has. (The same strategy can be applied to otherways of separating levels of properties, like themicro/macro distinction.)The notions of emergence developed here are notions of emergencein a weak sense: the higher level emergent properties wecapture are always structural properties (or are realized insuch properties), that is, they are defined in terms of the lowerlevel properties and their relations. Diachronic and synchronicemergent properties are distinctions within thecategory of structural properties. (shrink)

Recent work in the Philosophy of Mind has suggested that alternatives to reduction are required in order to explain the relationship between psychology and biology or physics. Emergence has been proposed as one such alternative. In this paper, I propose a precise definition of emergence, and I argue that chaotic systems provide concrete examples of properties that meet this definition. In particular, I suggest that being in the basin of attraction of a strange attractor is an emergent property of any (...) chaotic nonlinear dynamical system. This shows that non-reductive accounts of inter-theoretic relations are necessary, and that non-reductive accounts of the mental are possible. Moreover, this work provides a foundation for future work investigating the nature of explanation, prediction, and scientific understanding of non-reductive phenomena. (shrink)

We will show that there is a strong form of emergence in cell biology. Beginning with C.D. Broad’s classic discussion of emergence, we distinguish two conditions sufficient for emergence. Emergence in biology must be compatible with the thought that all explanations of systemic properties are mechanistic explanations and with their sufficiency. Explanations of systemic properties are always in terms of the properties of the parts within the system. Nonetheless, systemic properties can still be emergent. If the properties of the components (...) within the system cannot be predicted, even in principle, from the behavior of the system’s parts within simpler wholes then there also will be systemic properties which cannot be predicted, even in principle, on basis of the behavior of these parts. We show in an explicit case study drawn from molecular cell physiology that biochemical networks display this kind of emergence, even though they deploy only mechanistic explanations. This illustrates emergence and its place in nature. (shrink)

We will show that there is a strong form of emergence in cell biology. Beginning with C.D. Broad's classic discussion of emergence, we distinguish two conditions sufficient for emergence. Emergence in biology must be compatible with the thought that all explanations of systemic properties are mechanistic explanations and with their sufficiency. Explanations of systemic properties are always in terms of the properties of the parts within the system. Nonetheless, systemic properties can still be emergent. If the properties of the components (...) within the system cannot be predicted, even in principle, from the behavior of the system's parts within simpler wholes then there also will be systemic properties which cannot be predicted, even in principle, on basis of the behavior of these parts. We show in an explicit case study drawn from molecular cell physiology that biochemical networks display this kind of emergence, even though they deploy only mechanistic explanations. This illustrates emergence and its place in nature. (shrink)

An innocent form of emergence—what I call "weak emergence"—is now a commonplace in a thriving interdisciplinary nexus of scientific activity—sometimes called the "sciences of complexity"—that include connectionist modelling, non-linear dynamics (popularly known as "chaos" theory), and artificial life.1 After defining it, illustrating it in two contexts, and reviewing the available evidence, I conclude that the scientific and philosophical prospects for weak emergence are bright.

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. (shrink)

NOW IN PAPERBACK"€"Starting from a collection of simple computer experiments"€"illustrated in the book by striking computer graphics"€"Stephen Wolfram shows how their unexpected results force a whole new way of looking at the operation of our universe.

The modern materialist approach to life has conspicuously failed to explain such central mind-related features of our world as consciousness, intentionality, meaning, and value. This failure to account for something so integral to nature as mind, argues philosopher Thomas Nagel, is a major problem, threatening to unravel the entire naturalistic world picture, extending to biology, evolutionary theory, and cosmology. Since minds are features of biological systems that have developed through evolution, the standard materialist version of evolutionary biology is fundamentally incomplete. (...) And the cosmological history that led to the origin of life and the coming into existence of the conditions for evolution cannot be a merely materialist history, either. An adequate conception of nature would have to explain the appearance in the universe of materially irreducible conscious minds, as such. Nagel's skepticism is not based on religious belief or on a belief in any definite alternative. In Mind and Cosmos, he does suggest that if the materialist account is wrong, then principles of a different kind may also be at work in the history of nature, principles of the growth of order that are in their logical form teleological rather than mechanistic. In spite of the great achievements of the physical sciences, reductive materialism is a world view ripe for displacement. Nagel shows that to recognize its limits is the first step in looking for alternatives, or at least in being open to their possibility. (shrink)

We describe a novel Internet-based method for building consensus and clarifying con icts in large stakeholder groups facing complex issues, and we use the method to survey and map the scienti c and organizational perspectives of the arti cial life community during the Seventh International Conference on Arti cial Life (summer 2000). The issues addressed in this survey included arti cial life’s main successes, main failures, main open scienti c questions, and main strategies for the future, as well as the (...) bene ts and pitfalls of creating a professional society for arti cial life. By illuminating the arti cial life community’s collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups. (shrink)