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)
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.
To surmount the notorious difficulties of defining life, we should evaluate theories of life not by whether they provide necessary and sufficient conditions for our current preconceptions about life but by how well they explain living phenomena and how satisfactorily they resolve puzzles about life. On these grounds, the theory of life as supple adaptation (Bedau 1996) gets support from its natural and compelling resolutions of the following four puzzles: (1) How are different forms of life at different levels of (...) the vital hierarchy related? (2) Is there a continuum between life and non-life? (3) Does life essentially concern a living entity’s material composition or its form? (4) Are life and mind intrinsically connected? (shrink)
Bringing together the latest scientific advances and some of the most enduring subtle philosophical puzzles and problems, this book collects original historical and contemporary sources to explore the wide range of issues surrounding the nature of life. Selections ranging from Aristotle and Descartes to Sagan and Dawkins are organised around four broad themes covering classical discussions of life, the origins and extent of natural life, contemporary artificial life creations and the definition and meaning of 'life' in its most general form. (...) Each section is preceded by an extensive introduction connecting the various ideas discussed in individual chapters and providing helpful background material for understanding them. With its interdisciplinary perspective, this fascinating collection is essential reading for scientists and philosophers interested in astrobiology, synthetic biology and the philosophy of life. (shrink)
Weak emergence has been offered as an explication of the ubiquitous notion of emergence used m complexity science After outlining the problem of emergence and comparing weak emergence with the two other weak objectivist approaches to emergence, the paper explains a version of weak emergence and illustrates at with cellular automata Then it explains the sort of downward causation and explanatory autonomy involved m weak emergence.
We consider how to discern whether or not evolution is taking place in an observed system. Evolution will be characterized in terms of a particular macroscopic behavior that emerges from microscopic organismic interaction. We de ne evolutionary activity as the rate at which useful genetic innovations are absorbed into the population. After measuring evolutionary activity in a simple model biosphere, we discuss applications to other systems. We argue that evolutionary activity provides an objective, quantitative interpretation of the intuitive idea of (...) biological teleology. We also propose using evolutionary activity in a test for life. (shrink)
We can readily identify goal-directed systems and distinguish them from non-goal-directed systems. A woodpecker hunting for grubs is the first, a pendulum returning to rest is the second. But what is it to be a goal-directed system? Perhaps the dominant answer to this question, inspired by systems theories such as cybernetics, is that goal-directed systems are distinguished by their tendency to seek, aim at, or maintain some more-or-less easily identifiable goal. Cybernetics and the like would hold that physical systems subject (...) only to physical laws can exhibit such behavior. If sound, this systems approach to teleology would unify a diverse range of goal-directed phenomena and neatly side-step many traditional bogey-men of teleology, such as anthropomorphism and future causation. Goal-directed phenomena would be a normal feature of the natural causal world that could be described in purely descriptive and quantitative terms, and receive ordinary causal explanations. Thus, the systems approach promises to provide a naturalistic-cum-descriptive account of teleology suitable for use in naturalistic accounts of other phenomena, including the intentionality of mental states and even self-consciousness. (shrink)
Artificial life (also known as “ALife”) is a broad, interdisciplinary endeavor that studies life and life-like processes through simulation and synthesis. The goals of this activity include modelling and even creating life and life-like systems, as well as developing practical applications using intuitions and methods taken from living systems. Artificial life both illuminates traditional philosophical questions and raises new philosophical questions. Since both artificial life and philosophy investigate the essential nature of certain fundamental aspects of reality like life and adaptation, (...) artificial life offers philosophy a new perspective on these phenomena. This chapter provides an introduction to current research in artificial life and explains its philosophical implications. (shrink)
This paper describes and defends the view that minimal chemical life essentially involves the chemical integration of three chemical functionalities: containment, metabolism, and program (Rasmussen et al. in Protocells: bridging nonliving and living matter, 2009a ). This view is illustrated and explained with the help of CMP and Rasmussen diagrams (Rasmussen et al. In: Rasmussen et al. (eds.) in Protocells: bridging nonliving and living matter, 71–100, 2009b ), both of which represent the key chemical functional dependencies among containment, metabolism, and (...) program. The CMP model of minimal chemical life gains some support from the broad view of life as open-ended evolution, which I have defended elsewhere (Bedau in The philosophy of artificial life, 1996 ; Bedau in Artificial Life, 4:125–140, 1998 ). Further support comes from the natural way the CMP model resolves the puzzle about whether life is a matter of degree. (shrink)
Artificial life uses computer models to study the essential nature of the characteristic processes of complex adaptive systems proceses such as self-organization, adaptation, and evolution. Work in the field is guided by the working hypothesis that simple computer models can capture the essential nature of these processes. This hypothesis is illustrated by recent results with a simple population of computational agents whose sensorimotor functionality undergo open-ended adaptive evolution. These might illuminate three aspects of complex adaptive systems in general: punctuated equilibrium (...) dynamics of diversity, a transition separating genetic order and disorder, and a law of adaptive evolutionary activity. (shrink)
There is a long history of cryptographic hash functions, i.e. functions mapping variable-length strings to fixed-length strings, and such functions are also expected to enjoy certain security properties. Hash functions can be effected via modular arithmetic, permutation-based schemes, chaotic mixing, and so on. Herein we introduce the notion of an artificial-life (ALife) hash function (ALHF), whereby the requisite mixing action of a good hash function is accomplished via ALife rules that give rise to complex evolution of a given system. Various (...) security tests have been run, and the results reported for examples of ALHFs. (shrink)
Top-down synthetic biology makes partly synthetic cells by redesigning simple natural forms of life, and bottom-up synthetic biology aims to make fully synthetic cells using only entirely nonliving components. Within synthetic biology the notions of complexity and emergence are quite controversial, but the imprecision of key notions makes the discussion inconclusive. I employ a precise notion of weak emergent property, which is a robust characteristic of the behavior of complex bottom-up causal webs, where a complex causal web is one that (...) is incompressible and its behavior cannot be derived except by crawling through all of the gory details of the interactions in the web. The central thesis of this article is that synthetic biology centrally is the activity of engineering the desired weak emergent properties of synthetic cells. Synthetic biology has many different ways to engineer desired weak emergent properties of synthetic cells, including Edisonian trial and error, standardized parts, refactoring, and reprogramming synthetic genomes. The article ends by noting two philosophical consequences of engineering weak emergence. One is epistemological: synthesis is crucial for discovering weak emergent properties. The other is metaphysical: simple life forms are nothing but complex chemical mechanisms. (shrink)
One can study the the evolution of sensorimotor functionality by synthesizing this process in an abstract arti cial life model, speci cally, a population of agents that interact with each other and with their environment in a way that allows natural selection implicitly to shape their sensorimotor couplings. The present paper de nes very general measures of environmental and sensory uncertainty, and of action's direct and indirect e ects on perception, and reports a series of observations of these quantities in (...) the context of the model. (shrink)
This paper describes and defends the view that minimal chemical life essentially involves the chemical integration of three chemical functionalities: containment, metabolism, and program. This view is illustrated and explained with the help of CMP and Rasmussen diagrams in Protocells: bridging nonliving and living matter, 71–100, 2009b), both of which represent the key chemical functional dependencies among containment, metabolism, and program. The CMP model of minimal chemical life gains some support from the broad view of life as open-ended evolution, which (...) I have defended elsewhere. Further support comes from the natural way the CMP model resolves the puzzle about whether life is a matter of degree. (shrink)
We have studied the adaptation of mutation rates in a simple model of evolution. The model consists of a two-dimensional world with a periodically replenished resource and a uctuating population of evolving agents whose survival and reproduction are an implicit a function of their success at nding resources and their internal metabolism. Earlier work suggested that mutation rate is a control parameter that governs a transition between two qualitatively di erent kinds of complex adaptive systems, and that the power of (...) adaptive evolution is maximized when the mutation rate is around this transition. This paper provides evidence that evolving mutation rates adapt to values around this transition. Furthermore, the mutation rates adapt up (or down) as the evolutionary demands for novelty (or memory) increase. (shrink)
Ligation is a form of chemical self-assembly that involves dynamic formation of strong covalent bonds in the presence of weak associative forces. We study an extremely simple form of ligation by means of a dissipative particle dynamics (DPD) model extended to include the dynamic making and breaking of strong bonds, which we term dynamically bonding dissipative particle dynamics (DDPD). Then we use a chemical genetic algorithm (CGA) to optimize the model’s parameters to achieve a limited form of ligation of trimers—a (...) proof of principle for the evolutionary design of self-assembling chemical systems. (shrink)
The dynamical patterns in mental phenomena have a characteristic suppleness&emdash;a looseness or softness that persistently resists precise formulation&emdash;which apparently underlies the frame problem of artificial intelligence. This suppleness also undermines contemporary philosophical functionalist attempts to define mental capacities. Living systems display an analogous form of supple dynamics. However, the supple dynamics of living systems have been captured in recent artificial life models, due to the emergent architecture of those models. This suggests that analogous emergent models might be able to explain (...) supple dynamics of mental phenomena. These emergent models of the supple mind, if successful, would refashion the nature of contemporary functionalism in the philosophy of mind. (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)
Those interested in the relationship betw een environment structure and behavior — the topic of this special issue of Adaptive Behavior — w ill find much of value in Peter Godfrey-Smith's new book, Complexity and the Function of Mind in Nature (hereafter CFMN; all page citations are to CFMN unless otherw ise indicated). The w riting is clear and concise, aptly balancing precision and breadth, and a host of relevant issues are raised and advanced. Although my comments here w ill (...) focus only on the book's fundamental conceptual framew ork for how organisms relate to their environments, I enthusiastically recommend the entire book. (shrink)
The robust behavior of the patent citation network is a complex target of recent bottom-up models in science. This paper investigates the purpose and testing of three especially simple bottom-up models of the citation count distribution observed in the patent citation network. The complex causal webs in the models generate weakly emergent patterns of behavior, and this explains both the need for empirical observation of computer simulations of the models and the epistemic harmlessness of the resulting epistemic opacity.
This paper investigates how environmental structure, given the innate properties of a population, affects the degree to which this population can adapt to the environment. The model we explore involves simple agents in a 2-d world which can sense a local food distribution and, as specified by their genomes, move to a new location and ingest the food there. Adaptation in this model consists of improving the genomic sensorimotor mapping so as to maximally exploit the environmental resources. We vary environmental (...) structure to see its specific effect on adaptive success. In our investigation, two properties of environmental structure, conditioned by the sensorimotor capacities of the agents, have emerged as significant factors in determining adaptive success: (1) the information content of the environment which quantifies the diversity of conditions sensed, and (2) the expected utility for optimal action. These correspond to the syntactic and pragmatic aspects of environmental information, respectively. We find that the ratio of expected utility to information content predicts adaptive success measured by population gain and information content alone predicts the fraction of ideal utility achieved. These quantitative methods and specific conclusions should aid in understanding the effects of environmental structure on evolutionary adaptation in a wide range of evolving systems, both artificial and natural. (shrink)
The new interdisciplinary science of artificial life has had a connection with the arts from its inception. This paper provides an overview of artificial life, reviews its key scientific challenges, and discusses its philosophical implications. It ends with a few words about the implications of artificial life for the arts.
The aim of this chapter is to show how the technological research activity called “artificial life” is shedding new light on human creativity. Artificial life aims to understanding the fundamental behavior of life-like systems by synthesizing that behavior in artificial systems (more on artificial life below). One of the most interesting behaviors of living systems is their creativity. Biological creativity can be found in both individual living organisms and in the whole biosphere—the entire interconnected system comprised of all forms of (...) life—but I will focus in this chapter on the biological creativity exhibited by the evolutionary process. This is the creativity that enabled the earliest simple life forms to spontaneously evolve into the incredibly rich and beautiful diversity of life that now surrounds us. This diversity of life includes the most complex adaptive and intelligent systems in the known universe. This is an amazingly powerful spontaneous creation process, indeed. I will refer to it as hyper-creativity to call attention to the way in which it produces qualitatively new and more complex kinds of adaptations. There is a similar quality in human creativity. I am thinking of the aesthetic and cultural creativity of artists, but also the intellectual creativity of scientists and scholars, as well as the commercial and practical creativity of craftsmen, businessmen, and entrepreneurs. And I want to focus especially on the hyper- creative aspects of human creativity—the way in which human activity can yield qualitatively new and more complex creations. (shrink)
The nature and status of psychological laws are a long-standing controversy. I will argue that part of the controversy stems from the distinctive nature of an important subset of those laws, which I’ll call “supple laws.” An emergent-model strategy taken by the new interdisciplinary field of artificial life provides a strikingly successful understanding of analogously supple laws in biology. So, after reviewing the failures of the two evident strategies for understanding supple psychological laws, I’ll turn for inspiration to emergent-models explanations (...) of supple laws in biology. I’ll conclude by inferring what an emergent model of supple laws in psychology should be like. (shrink)
Evolvability is the capacity to create new adaptations, and especially new kinds of adaptations, through the evolutionary process. Evolvability is important both as a theoretical issue in biology and as a practical issue in evolutionary computation. But it is difficult to study evolvability, in part because it is difficult to..
Evolutionary activity statistics and their visualization are introduced, and their motivation is explained. Examples of their use are described, and their strengths and limitations are discussed. References to more extensive or general accounts of these techniques are provided.
This paper concerns the relationship between the detectable and useful structure in an environment and the degree to which a population can adapt to that environment. We explore the hypothesis that adaptability will depend unimodally on environmental variety, and we measure this component of environmental structure using the information-theoretic uncertainty of detectable environmental conditions. We de ne adaptability as the degree to which a certain kind of population successfully adapts to a certain kind of environment, and we measure adaptability by (...) comparing a population's size to the size of a non-adapting, but otherwise comparable, population in the same environment. We study the relationship between adaptability and environmental structure in an evolving arti cial population of sensorimotor agents that live, reproduce, and die in a variety of environments. We nd that adaptability does not show a unimodal dependence on environmental variety alone, although there is justi cation for preserving our unimodal hypothesis if we consider other aspects of environmental structure. In particular, adaptability depends not just on how much structural information is detectable in the environment, but also on how unambiguous and valuable this information is, i.e., whether the information accurately signals a di erence that makes a di erence. How best to measure and integrate these other components of environmental structure remains unresolved. (shrink)
artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated.
We use game theory and Santa Fe Artificial Stock Market, an agent-based model of an evolving stock market, to study the optimal frequency for traders to revise their market forecasting rules. We discover two things: There is a unique strategic Nash equilibrium in the game of choosing forecast revision rates, and this equilibrium is sub-optimal in the sense that traders’ earnings are not maximized an the market is inefficient. This strategic equilibrium is due to an analogue of the prisoner’s dilemma; (...) the optimal global state is unstable because each trader has too much incentive to ‘defect’ and use forecasting rules that pull the market into thesub-optimal equilibrium. (shrink)
There are at least two different ways in which values and science can be connected. One is through the evaluation of science, and the other is through the scientific investigation of values. The evaluation of science is a non−scientific, political or ethical investigation of the practices of science. Various proposed and actual scientific practices call out for social and ethical evaluation. A few that have received recent attention are the human genome project, intelligence testing, and encryption algorithms. Such evaluations of (...) science contrasts sharply with what I call "the science of values." This is not one science or even one unified nexus of scientific activities but a loosely defined grab bag containing all scientific investigations of matters involving values. (shrink)