John Collier

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

Information is commonly understood as knowledge or facts acquired or derived from, e.g., study, instruction or observation (Macmillan Contemporary Dictionary, 1979). On this notion, information is presumed to be both meaningful and veridical, and to have some appropriate connection to its object; it is concerned with representations and symbols in the most general sense MacKay 1969 ). Information might be misleading, but it can never be false. Deliberately misleading data is misinformation. The scientific notion of information abstracts from the representational idea, and includes anything that could potentially serve as a source of information. The most fundamental notion of information, attributed to a number of different authors, is "a distinction that makes a difference" MacKay 1969 ), or "a differnece that makes a difference" Bateson 1973 : 428). Information theory, then, is fundamentally the rigorous study of distinctions and their relations, inasmuch as they make a difference

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.

Formal pragmatics plays an important, though secondary, role in modern analytical philosophy of language: its aim is to explain how context can affect the meaning of certain special kinds of utterances. During recent years, the adequacy of formal tools has come under attack, often leading to one or another form of relativism or antirealism.1 Our aim will be to extend the critique to formal pragmatics while showing that sceptical conclusions can be avoided by developing a different approach to the issues. In particular, we will show that formal pragmatics cannot provide a complete account of how context affects the meaning of utterances, both on its own terms and when faced with evidence of important aspects of natural languages. The focal issue is the relevant kind of context in which pragmatics should examine utterances. Our contention will be that the relevant context of an utterance is determined by the function of that utterance, this function being dependent upon the primary function of language – to convey information. We will argue that the functions of utterances and of language are too broad to be caught by the tools of formal pragmatics of the sort advocated by Montague (1968, 1974), which are an extension the methods of traditional model-theoretic semantics.2 The particular formal approach we will use as the main example is David Kaplan’s position (1979, 1989),3 an extension of Montague’s program

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.

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

We find symmetry attractive. It is often an indicator of the deep structure of things, whether they be natural phenomena, or artificial. 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. On the other hand, symmetries represent a kind of invariance under transformation, i.e., 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? Rhythmic entrainment is the formation of regular, predictable patterns in time and/or space through interactions within or between systems (resulting in symmetry). The result of entrainment is a simplification of the entrained system. It is the complement to symmetry breaking. Entrainment can be either forced or spontaneous, with the spontaneous form being uncontrollable. It results from processes that are called self-organising. Interestingly, spontaneous entrainment require much less power to form and maintain. It is also the source of levels in systems. I finish with some observations for social systems

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.

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.

Function refers to a broad family of concepts of varying abstractness and range of application, from a many-one mathematical relation of great generality to, for example, highly specialized roles of designed elements in complex machines such as degaussing in a television set, or contributory processes to control mechanisms in complex metabolic pathways, such as the inhibitory function of the appropriate part of the lac-operon on the production of lactase through its action on the genome in the absence of lactose. We would like a language broad enough, neutral enough, but yet powerful enough to cover all such cases, and at the same time to give a framework form explanation both of the family resemblances and differences. General logic and mathematics are too abstract, but more importantly, too broad, whereas other discourses of function, such as the biological and teleological contexts, are too narrow. Information is especially suited since it is mathematically grounded, but also has a wellknown physical interpretation through the Schr dinger/Brillouin Negentropy Principle of Information, and an engineering or design interpretation through Shannon's communication theory. My main focus will be on the functions of autonomous anticipatory systems, but I will try to demonstrate both the connections between this notion of function and the others, especially to dynamical systems with a physical interpretation on the one side and intentional systems on the other. The former are based in concepts like force, energy and work, while the latter involve notions like representation, control and purpose, traditionally, at least in Modern times, on opposite sides of the Cartesian divide. In principle, information can be reduced to energy, but it has the advantage of being more flexible, and easier to apply to higher level phenomena