John Collier

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..

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..

Functionality is essential to any form of anticipation beyond simple directedness at an end. In the literature on function in biology, there are two distinct approaches. One, the etiological view, places the origin of function in selection, while the other, the organizational view, individuates function by organizational role. Both approaches have well-known advantages and disadvantages. I propose a reconciliation of the two approaches, based in an interactivist approach to the individuation and stability of organisms. The approach was suggested by Kant in the Critique of Judgment, but since it requires, on his account, the identification a new form of causation, it has not been accessible by analytical techniques. I proceed by construction of the required concept to fit certain design requirements. This construction builds on concepts introduced in my previous four talks to these meetings.

In Robert West’s talk last week, dynamical systems theory (DST) was applied to a specific problem involving interacting symbolic systems, without much reference to how those systems are embodied or related to other types of systems. Despite this level of abstraction, DST can yield interesting results, though one might be left wondering if it really leads to understanding, or what it all means. In particular, Robert noted problems he has in convincing referees that the sort of explanation he gave can give a useful understanding, and that it doesn’t invoke dubious notions with its references to emergence, holism, and mathematical openness.

In this critical notice, I argue that the semantic view championed by Thompson no logical advantage over the syntactic view of theories, especially in the area of interpretation. Each weakness of the syntactic view has a corresponding weakness in the semantic view. In principle the two are not different in power, but it is sometimes better to adopt one rather than the other, for practical reasons. I agree with Thompson that many issues in the philosophy of biology can be illuminated by the semantic view, but that other things, especially deriving specific prediction, are best understood with the syntactic view.

Systematics, along with the other comparative biological sciences and certain astronomical disciplines, is much more concerned with form and organization than other biological and physical sciences, in which dynamics plays the central role. Within the biological sciences, Nelson (1970) characterizes disciplines that study diversity and patterns “comparative” and those that search for process and dynamics “general.” The goal of “general” science is to uncover the mechanisms that unify observed phenomena. Whether the physicist sees herself, like Newton (1953: 3-5), to be discovering fundamental causal explanations, or like Duhem (1962: 19-30), to be uncovering a natural classification, dynamical concepts referring to essentially hidden processes are indispensable. Much of comparative biology, in contrast, is primarily descriptive, with explanations taking a secondary role, at least until the diversity is described and comparisons made. Unlike the general sciences, in which elegance and quantitative analysis have long been major indicators of truth, the comparative sciences stress complexity, happenstance and qualitative analysis. In systematics in particular, theory and explanation are often thought to play a minimal role, if any at all1.

Daniel R. Brooks and E. O. Wiley have proposed a theory of evolution in which fitness is merely a rate determining factor. Evolution is driven by non-equilibrium processes which increase the entropy and information content of species together. Evolution can occur without environmental selection, since increased complexity and organization result from the likely capture at the species level of random variations produced at the chemical level. Speciation can occur as the result of variation within the species which decreases the probability of sharing genetic information. Critics of the Brooks-Wiley theory argue that they have abused terminology from information theory and t thermodynamics. In this paper I review the essentials of the theory, and give an account of hierarchical physical information systems within which the theory can be interpreted. I then show how the major conceptual objections can be answered.

Supervenience is a relationship which has been used recently to explain the physical determination of biological phenomena despite resistance to reduction. Supervenience, however, is plagued by ambiguities which weaken its explanatory value and obscure some interesting aspects of reduction in biology. Although I suspect that similar considerations affect the use of supervenience in ethics and the philosophy of mind, I don’t intend anything I have to say here to apply outside of the physical and biological cases I consider.The main point of this paper is that there is a property of biological systems which makes it both misleading and inappropriate to reduce central biological phenomena to the properties of underlying components. Despite this, reductive explanation has been a major source of innovation in biological theory. The apparent tension can be resolved if underlying properties are explanatorily relevant to the higher level phenomena even though the latter are not strictly reducible to the former. Supervenience, I will argue, is not robust enough to deny reduction while supporting explanatory relevance.

The subject of this chapter is the identity of individual dynamical objects and properties. Two problems have dominated the literature: transtemporal identity and the relation between composition and identity. Most traditional approaches to identity rely on some version of classification via essential or typical properties, whether nominal or real. Nominal properties have the disadvantage of producing unnatural classifications, and have several other problems. Real properties, however, are often inaccessible or hard to define (strict definition would make them nominal). I suggest that classification should be in terms of dynamical properties of systems, starting with individual systems rather than classes, and working up by abstractions that fit causal generalities. The advantage of this approach is that individuality is testable and revisable as we come to know more about systems. Another advantage is that if anything is real, then it is the dynamical. Once I have presented this approach in general, I will show that the central concept of dynamical cohesion (the "dividing glue") is amenable to giving a principled account of individuation as a process, at the same time explaining the origin of diversity. Some other advantages of this approach are presented, including how it can be used as a basis for testable classifications. This last has moral implications, since cohesion at the individual and the social levels, and their interactions, can impinge on proper moral decisions.

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.

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?

Both natural and engineered systems are fundamentally dynamical in nature: their defining properties are causal, and their functional capacities are causally grounded. Among dynamical systems, an interesting and important sub-class are those that are autonomous, anticipative and adaptive (AAA). Living systems, intelligent systems, sophisticated robots and social systems belong to this class, and the use of these terms has recently spread rapidly through the scientific literature. Central to understanding these dynamical systems is their complicated organisation and their consequent capacities for re- and self- organisation. But there is at present no general analysis of these capacities or of the requisite organisation involved. We define what distinguishes AAA systems from other kinds of systems by characterising their central properties in a dynamically interpreted information theory.

Since the origins of the notion of emergence in attempts to recover the content of vitalistic anti-reductionism without its questionable metaphysics, emergence has been treated in terms of logical properties. This approach was doomed to failure, because logical properties are either sui generis or they are constructions from other logical properties. If the former, they do not explain on their own and are inevitably somewhat arbitrary (the problem with the related concept of supervenience, Collier, 1988a), but if the latter, reducibility is assured because logical constructs are reducible, by definition, to their logical components. A satisfactory account of emergence must recognise that it is a dynamical, not a logical property of property of natural systems, and that its basis is dynamical rather than logical composition. Collier (1988a) introduced the concept of cohesion as the closure of the causal relations among the dynamical parts of a dynamical particular that determine its resistance to external and internal fluctuations that might disrupt its integrity. Cohesion is an equivalence relation that partitions a set of dynamical particulars into unified and distinct entities, providing the identity conditions for such particulars. Cohesion blocks reduction of dynamical particulars, and is necessary for dynamical emergence. We will give reasons for thinking that cohesion might be sufficient for emergence as well.

Complex systems are dynamic and may show high levels of variability in both space and time. It is often difficult to decide on what constitutes a given complex system, i.e., where system boundaries should be set, and what amounts to substantial change within the system. We discuss two central themes: the nature of system definitions and their ability to cope with change, and the importance of system definitions for the mental metamodels that we use to describe and order ideas about system change. Systems can only be considered as single study units if they retain their identity. Previous system definitions have largely ignored the need for both spatial and temporal continuity as essential attributes of identity. After considering the philosophical issues surrounding identity and system definitions, we examine their application to modeling studies. We outline a set of five alternative metamodels that capture a range of the basic dynamics of complex systems. Although Holling’s adaptive cycle is a compelling and widely applicable metamodel that fits many complex systems, there are systems that do not necessarily follow the adaptive cycle. We propose that more careful consideration of system definitions and alternative metamodels for complex systems will lead to greater conceptual clarity in the field and, ultimately, to more rigorous research.

We argue that living systems process information such that functionality emerges in them on a continuous basis. We then provide a framework that can explain and model the normativity of biological functionality. In addition we offer an explanation of the anticipatory nature of functionality within our overall approach. We adopt a Peircean approach to Biosemiotics, and a dynamical approach to Digital-Analog relations and to the interplay between different levels of functionality in autonomous systems, taking an integrative approach. We then apply the underlying biosemiotic logic to a particular biological system, giving a model of the B-Cell Receptor signaling system, in order to demonstrate how biosemiotic concepts can be used to build an account of biological information and functionality. Next we show how this framework can be used to explain and model more complex aspects of biological normativity, for example, how cross-talk between different signaling pathways can be avoided. Overall, we describe an integrated theoretical framework for the emergence of normative functions and, consequently, for the way information is transduced across several interconnected organizational levels in an autonomous system, and we demonstrate how this can be applied in real biological phenomena. Our aim is to open the way towards realistic tools for the modeling of information and normativity in autonomous biological agents.

Evolutionary moral realism is the view that there are moral values with roots in evolution that are both specifically moral and exist independently of human belief systems. In beginning to sketch the outlines of such a view, we examine moral goods like fairness and empathetic caring as valuable and real aspects of the environments of species that are intelligent and social, or at least developing along an evolutionary trajectory that could lead to a level of intelligence that would enable individual members of the species to recognize and respond to such things as the moral goods they in fact are. We suggest that what is most morally interesting and important from a biological perspective is the existence and development of such trajectories, rather than the position of one particular species, such as our own, on one particular trajectory.

Speculation about the evolutionary origins of morality has yet to show how a biologically based capacity for morality might be connected to moral reasoning. Applying an evolutionary approach to three kinds of cases where partiality may or may not be morally reasonable, this paper explores a possible connection between a psychological capacity for morality and processes of wide reflective moral equilibrium. The central hypothesis is that while we might expect a capacity for morality to include aspects of partiality, we might also expect these same aspects of the capacity to produce systemic forms of performance-based error. Understanding these errors helps point the way toward a theory of moral competence that includes aspects of both partiality and impartiality.