Mark Bedau

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.

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 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.

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?

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.

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.

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.

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.

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.

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?

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.

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”.

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.

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.

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.