John Collier

Complexly organized systems include biological and cognitive systems, as well as many of the everyday systems that form our environment. They are both common and important, but are not well understood. A complex system is, roughly, one that cannot be fully understood via analytic methods alone. An organized system is one that shows spatio-temporal correlations that are not determined by purely local conditions, though organization can be more or less localizable within a system. Organization and complexity can vary independently to some extent, but they are interconnected: organisation requires some complexity, but complexity cannot be maximum in an organized system. I will define complexity and organization more precisely, and show how these definitions imply the above properties. Next I will discuss how organized complexity can be modelled, with an eye to limitations on the tractability of both the models and the modelling process. I will finish with some remarks on the limits of our possible understanding of complexly organized systems. Keywords: complexity, organization, modelling, holism, information theory..

We find symmetry attractive. It interests us. Symmetry is often an indicator of the deep structure of things, whether they be natural phenomena, or the creations of artists. For example, the most fundamental conservation laws of physics are all based in symmetry. Similarly, the symmetries found in religious art throughout the world are intended to draw attention to deep spiritual truths. Not only do we find symmetry pleasing, but its discovery is often also surprising and illuminating as well. For these reasons, we are inclined to think that symmetries are informative, and that symmetries contain information. On the other hand, symmetries represent a kind of invariance under transformation. Such invariance implies that symmetrical things contain redundancies. Redundancy, in turn, implies that the information content of a symmetrical structure or configuration is less than that of a similar nonsymmetrical structure. Symmetry, then, entails a reduction in information content. These considerations present us with somewhat of a paradox: On the one hand, many symmetries that we find in the world are surprising, and surprise indicates informativeness. On the other hand, the surprise value of information arises because it presents us with the unexpected or improbable, but symmetries, far from creating the unexpected, ensure that the known can be extended through invariant transformations. How can this paradox be resolved?

Developments in science in the last few decades have led to doubts about the validity of the mechanical paradigm that has dominated science since the Scientific Revolution. The new views, coming from recently founded disciplines like non-equilibrium thermodynamics, chaos theory and the theory of dynamical systems, are rooted in physics. Nonetheless, much of their motivation comes from fields as diverse as weather prediction, ecology, economics, the study of traffic flow, and the growth of cities. Although Quantum Mechanics also led to doubts about the validity of the mechanical paradigm, the new views reveal problems within classical physics itself. The implications of these developments for our understanding of space have been largely unexamined. But the close connection between the Newtonian view of space and the mechanical paradigm means that the demise of the mechanical paradigm will require a re-evaluation of our understanding of physical space.

It is generally agreed that organisms are Complex Adaptive Systems. Since the rise of Cybernetics in the middle of the last century ideas from information theory and control theory have been applied to the adaptations of biological organisms in order to explain how they work. This does not, however, explain functionality, which is widely but not universally attributed to biological systems. There are two approaches to functionality, one based on etiology (what a trait was selected for), and the other based in autonomy. I argue that the etiological approach, as understood in terms of control theory, suffers from a problem of symmetry, by which function can equally well be placed in the environment as in the organism. Focusing on the autonomy view, I note that it can be understood to some degree in terms of control theory in its version called second order cybernetics. I present an approach to second order cybernetics that seems plausible for organisms with limited computational power, due to Hooker, Penfold and Evans. They hold that this approach gives something like concepts, certainly abstractions from specific situations, a trait required for functionality in its system adaptive form (i.e., control of the system by itself). Using this cue, I argue that biosemiotics provides the methodology to incorporate these quasi concepts into an account of functionality.

The purpose of this paper is to describe some limitations on scientific behaviorist and computational models of the mind. These limitations stem from the inability of either model to account for the integration of experience and behavior. Behaviorism fails to give an adequate account of felt experience, whereas the computational model cannot account for the integration of our behavior with the world. Both approaches attempt to deal with their limitations by denying that the domain outside their limits is a part of psychology. These attempts to turn the shortcomings of the two models into virtues would be more convincing if their limitations were not diametrically opposed. I will argue that in each case the limitations are too restrictive unless the theories are augmented by physiology

Anticipation allows a system to adapt to conditions that have not yet come to be, either externally to the system or internally. Autonomous systems actively control the conditions of their own existence so as to increase their overall viability. This paper will first give minimal necessary and sufficient conditions for autonomous anticipation, followed by a taxonomy of autonomous anticipation. In more complex systems, there can be semi-autonomous subsystems that can anticipate and adapt on their own. Such subsystems can be integrated into a system’s overall autonomy, typically with greater efficiency due to modularity and specialization of function. However, it is also possible that semi-autonomous subsystems can act against the viability of the overall system, and have their own functions that conflict with overall system functions

Integrating concepts of maintenance and of origins is essential to explaining biological diversity. The unified theory of evolution attempts to find a common theme linking production rules inherent in biological systems, explaining the origin of biological order as a manifestation of the flow of energy and the flow of information on various spatial and temporal scales, with the recognition that natural selection is an evolutionarily relevant process. Biological systems persist in space and time by transfor ming energy from one state to another in a manner that generates structures which allows the system to continue to persist. Two classes of energetic transformations allow this; heat-generating transformations, resulting in a net loss of energy from the system, and conservative transformations, changing unusable energy into states that can be stored and used subsequently. All conservative transformations in biological systems are coupled with heat-generating transformations; hence, inherent biological production, or genealogical proesses, is positively entropic. There is a self-organizing phenomenology common to genealogical phenomena, which imparts an arrow of time to biological systems. Natural selection, which by itself is time-reversible, contributes to the organization of the self-organized genealogical trajectories. The interplay of genealogical (diversity-promoting) and selective (diversity-limiting) processes produces biological order to which the primary contribution is genealogical history. Dynamic changes occuring on times scales shorter than speciation rates are microevolutionary; those occuring on time scales longer than speciation rates are macroevolutionary. Macroevolutionary processes are neither redicible to, nor autonomous from, microevolutionary processes.

We propose an objective and justifiable ethics that is contingent on the truth of evolutionary theory. We do not argue for the truth of this position, which depends on the empirical question of whether moral functions form a natural class, but for its cogency and possibility. The position we propose combines the advantages of Kantian objectivity with the explanatory and motivational advantages of moral naturalism. It avoids problems with the epistemological inaccessibility of transcendent values, while avoiding the relativism or subjectivism often associated with moral naturalism. Our position emerges out of criticisms of the contemporary sociobiological views of morality found in the writings of Richard Alexander, Michael Ruse, and Robert Richards.

A major goal of science is to discover laws that underlie all regular phenomena. This goal is best satisfied by eternal principles that leave fundamental properties unchanged and unchangeable. Science has been forced to accept that some processes, especially biological processes, are inherently time oriented. It can either forgo the ideal of universal principles, and account for temporality through specific boundary conditions, or else incorporate the sources of change directly into fundamental principles that are the same for all times and places, and for all temporal scales. In the past, unifying principles adequate for biology have caused trouble for physics, and vice versa. Recent work at the intersection of non-equilibrium statistical mechanics and information theory suggests that physics and biology can finally be reconciled

Richard Alexander's second book on biology and morality is a continuation and amplification of the project he reported on in Darwinism and Human Affairs1. The Biology of Moral Systems is more abstract than the earlier book. It does not broach any new empirical ground, but puts Alexander's views into a broader context of philosophical and sociological discussions of morality. It discusses and criticizes alternative philosophical and biological views of morality, and presents his views on the significance of biology to moral issues in law, democracy and pursuit of the Good. In one interesting section that I will not be able to discuss here, Alexander provides an evolutionary hypothesis to explain each of Kohlberg's stages of moral development (pp. 131ff). The book ends with a discussion of some specific moral problems

Anticipation allows a system to adapt to conditions that have not yet come to be, either externally to the system or internally. Autonomous systems actively control their own conditions so as to increase their functionality (they self-regulate). Living systems self-regulate in order to increase their own viability. These increasingly stronger conditions, anticipation, autonomy and viability, can give an insight into progressively stronger classes of models of autonomy. I will argue that stronger forms are the relevant ones for Artificial Life. This has consequences for the design of and accurate simulation of living systems. Keywords: autonomy, modelling, function, simulation, anticipation, emergence DUBOIS’ CONJECTURE Autonomy basically means self-regulation. Self-regulation implies internal control of system states to achieve greater functionality, either internally or interactively with the environment. Functionality, as a teleological notion, implies that the system must be directed by likely future states; that is, it must anticipate and (possibly) adapt to likely future states. Functionality does not require autonomy (assuming functional goals are externally set), but merely that current states of the system can select suitable future states on the basis of suitable input. In this..

There are a number of different species concepts currently in use. The variety results from differing desiderata and practices of taxonomists, ecologists and evolutionary theorists. Recently, arguments have been presented for pluralism about species. I believe this is unsatisfactory, however, because of the central role of species in biological theory. Taking the line that species are individuals, I ask what might individuate them. In other work I have argued that dynamical systems are individuated by their cohesion. I present here a version of a cohesion concept of species that accounts for the advantages of other species concepts, and is open-ended enough to accommodate additions to or changes in biological theory. On my account biological forces combine like Newtonian forces, to work on a common locus. Just as we might have an electromagnetic system, we might have an ecological species, if the dominant source of cohesion is ecology, but there is no certainty that biological species will divide up into elegant single principle types anymore than there is for physical systems

Rhythmic entrainment is the formation of regular, predictable patterns in time and/or space through interactions within or between systems that manifest potential symmetries. We contend that this process is a major source of symmetries in specific systems, whether passive physical systems or active adaptive and/or voluntary/intentional systems, except that active systems have more control over accepting or avoiding rhythmic entrainment. The result of rhythmic entrainment is a simplification of the entrained system, in the sense that the information required to describe it is reduced. Entrainment can be communicated, passing information from one system to another. The paradigm is a group of jazz percussionists agreeing on a complex musical progression. The process of rhythmic entrainment is complementary to that of symmetry breaking, which produces information. The two processes account for much, if not all, of the complexity and organization in the universe. Rhythmic entrainment can be more or less spontaneous, with the completely spontaneous form being uncontrollable. A balance between the two forms can produce a more robust system, requiring less energy to maintain, whether in physical, biological or social systems. We outline some applications in physics, chemistry, biology, measurement and communication, ending with the especially interesting case of social and economic order. First though, we must introduce some basic principles

Examples of successful linguistic communication give rise to two important insights: (1) it should be understood most fundamentally in terms of the pragmatic success of each individual utterance, and (2) linguistic conventions need to be understood as on a par with the non-linguistic regularities that competent language users rely upon to refer. Syntax and semantics are part of what Barwise and Perry call the context of the utterance, contributing to the pragmatics of the utterance. This full and distributed multichannel context determines meaning if anything does. On the standard account of context, context disambiguates the meaning of language, but it is at least as apt in many situations to say that language disambiguates context. In practice, the two work together, sometimes with more emphasis on one than the other. Reference should be understood in pragmatic terms (it is an act) and, since success is often achieved in non-standard, creative ways, any formalisation of pragmatics can only be partial. The need for such an inventive approach to referring traces back to the need for language to be highly efficient, with expressions underdetermining their interpretation. Next, the shared semantic and syntactic regularities, which might seem to be independent of the context of an utterance, should be understood as also being part of that context. Past usage underdetermines how terms can be used since it allows for multiple projections. Successful reference with novel uses that are disambiguated by context can become the ground for new conventions.