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.

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)

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)

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)

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)

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 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 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)

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)

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)

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)

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)

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.

We study the effects of environmental catastrophes on the evolution of a population of sensory-motor agents with individually evolving mutation rates, and compare these effects in a variety of control systems. A catastrophe makes the balance shift toward the need for evolutionary novelty, and we observe the mutation rate evolve upwards. As the population adapts the sensory-motor strategies to the new environment and the balance shifts toward a need for evolutionary memory, the mutation rate falls. These observations support the hypothesis (...) that second-order evolution of the mutation flexibly balances the need for evolutionary “novelty” and “memory,” both of which are controlled by the mutation rate. (shrink)

The nature and status of cultural evolution and its connection with biological evolution are controversial in part because of Richard Dawkin’s suggestion that the scientific study of culture should include “memetics,” an analog of genetics in which genes are replaced by “memes”—the hypothetical units of cultural evolution. Memetics takes different forms; I focus on its minimal form, which claims merely that natural selection shapes to some extent the evolution of some aspects of culture. Advocates and critics of memetics disagree about (...) the scientific status of memetics, but they agree that memetics must face the following fundamental problems. Problem 1: Cultural evolution differs too much from biological evolution. Problem 2: Culture is too complex. Problem 3: Memes are too difficult to identify and track. Problem 4: Memetics produces only trivial results. This paper examines these problems in the context of a minimal memetic analysis in one specific context: patented inventions. Technology is a special subset of culture, and patented inventions are a special subset of technology—not least because there is a detailed written record of every patent. I describe four recent empirical results on technological innovation derived from memetic analysis of the patent record. Result 1: Inkjet printing, PCR, and stents are key drivers of technological innovation. Result 2: Patent genealogies are tangled and incestuous. Result 3: Door-opening innovations drive the evolution of technology. Result 4: The evolving content of the drivers of innovation confirms the importance of inkjet printing, PCR, and stents, among other inventions. These results show that minimal memetics can provide a novel and illuminating analysis the evolution of patented technology. Furthermore, this memetic analysis can answer all of the main problems with memetics. Problem 1 can be dismissed because culture and biology can be quite disanalogous, provided that natural selection still operates in both. Problem 2 is a mirage, because memetic analysis of the patented inventions is consistent with the full richness and complexity of the evolution of technology. Problem 3 is easy to solve, because the patent record makes it trivial to identify and track patents and their key traits through lineages. Problem 4 can be fully answered only after memetic analysis becomes widespread, but the results reviewed here shows that minimal memetics does yield scientific results that are nontrivial and interesting. (shrink)

We demonstrate a method for optimizing desired functionality in real complex chemical systems, using a genetic algorithm. The chemical systems studied here are mixtures of amphiphiles, which spontaneously exhibit a complex variety of self-assembled molecular aggregations, and the property optimized is turbidity. We also experimentally resolve the fitness landscape in some hyper-planes through the space of possible amphiphile formulations, in order to assess the practicality of our optimization method. Our method shows clear and significant progress after testing only 1 % (...) of the possible amphiphile formulations. (shrink)