The document contains fourteen pictures of waves of evolutionary activity created by alleles in the sensory-motor strategies of agents in Packard's Scatter model.1 The quality of these waves indicate di erent kinds of evolutionary phenomena involving signi cant adaptations in sensory-motor rules. The purpose of this document is only to depict a variety of kinds of evolutionary phenomena, not to explain those phenomena a job for another occasion. The following papers contain more background on evolutionary activity waves and Packard's Scatter (...) model. (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)
Artificial life attempts to understand the essential general properties of living systems by synthesizing life-like behavior in software, hardware and biochemicals. As many of the essential abstract properties of living systems (e.g. autonomous adaptive and intelligent behavior) are also studied by cognitive science, artificial life and cognitive science have an essential overlap. This review highlights the state of the art in artificial life with respect to dynamical hierarchies, molecular selforganization, evolutionary robotics, the evolution of complexity and language, and other practical (...) applications. It also speculates about future connections between artificial life and cognitive science. (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)
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..
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)
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)
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)
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)
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.
Systems Science Ph.D. Program, Portland State University, Portland, Oregon 97207-0751, jeff@sysc.pdx.edu Department of Philosophy, Reed College, 3203 SE Woodstock Boulevard, Portland, Oregon 97202, mab@reed.edu Systems Science Ph.D. Program, Portland State University, Portland, Oregon 97207-0751, zwick@sysc.pdx.edu..
Arti cial life studies computer models of the processes characteristic of complex adaptive systems|processes like self-organization, self-reproduction, adaptation, and evolution. Complex adaptive systems take many forms, each of which di ers from the others in myriad ways. By abstracting away from the diverse details, arti cial life hopes to reveal fundamental principles governing broad classes of complex adaptive systems. This hope rests on arti cial life's working hypoth-.
Contemporary artificial life (also known as “ALife”) is an interdisciplinary study of life and life-like processes. Its two most important qualities are that it focuses on the essential rather than the contingent features of living systems and that it attempts to understand living systems by artificially synthesizing extremely simple forms of them. These two qualities are connected. By synthesizing simple systems that are very life-like and yet very unfamiliar, artificial life constructively explores the boundaries of what is possible for life. (...) At the moment, artificial life uses three different kinds of synthetic methods. “Soft” artificial life creates computer simulations or other purely digital constructions that exhibit life-like behavior. “Hard” artificial life produces hardware implementations of life-like systems. “Wet” artifi- cial life involves the creation of life-like systems in a laboratory using biochemical materials. (shrink)
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)
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)
We study a new variant of the dissipative particle dynamics (DPD) model that includes the possibility of dynamically forming and breaking strong bonds. The emergent reaction kinetics may then interact with self-assembly processes. We observe that self-assembled amphiphilic aggregations such as micelles have a catalytic effect on chemical reaction networks, changing both equilibrium concentrations and reaction frequencies. These simulation results are in accordance with experimental results on the so-called “concentration effect”.
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 (Shannon entropy) 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)
We measure the environment that is relevant to a population's adaptation as the information-theoretic uncertainty of the distribution of local environmental states that the adapting population experiences. Then we observe the dynamics of this quantity in simple models of sensory-motor evolution, in which an evolving population of agents live, reproduce, and die in a two-dimensional world while competing for resources. Although the distribution of resources is static, the agents' evolution creates a dynamic environment for adaptation.
Systems Science Ph.D. Program, Portland State University, Portland, Oregon 97207-0751, jeff@sysc.pdx.edu Department of Philosophy, Reed College, 3203 SE Woodstock Boulevard, Portland, Oregon 97202, mab@reed.edu Systems Science Ph.D. Program, Portland State University, Portland, Oregon 97207-0751, zwick@sysc.pdx.edu..
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)
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)
We evaluate whether John Holland’s Echo model exemplifies his theory of complex adaptive systems. After reviewing Holland’s theory of complex adaptive systems and describing his Echo model, we describe and explain the characteristic evolutionary behavior observed in a series of Echo model runs. We conclude that Echo lacks the diversity of hierarchically organized aggregates that typify complex adaptive systems, and we explore possible explanations for this failure.
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)
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.
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)
The field of artificial life is enriching both the content and method of philosophy. One example of the impact of artificial life on the content of philosophy is the light it sheds on the perennial philosophical question of the nature of emergent pheonomena in general. Another second example is the way it highlights and promises to explain the suppleness of mental processes. Artificial life's computational thought experiments also provide philosophy with a methodological innovation. The limitations of the central arguments in (...) Stephen Jay Gould's.. (shrink)
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)
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)
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)
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.
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)
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)
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)
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)
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)
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)
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.
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)
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.
