John Collier

Every manifestation of information, semiosis and meaning we have been able to study experimentally has a physical form. Neglect of their dynamical (energetic) ground tends towards dualism or idealism, leaving the causal basis of semiosis and the causal powers of representations mysterious. Consideration of the necessary physical requirements for the embodiment of semiotic categories imposes a discipline on semiotics required for its integration into the rest of science, especially for the emerging field of biosemiotics, as well as any future extensions to chemistry physics or other realms that might constitute a general, primal semiotics. Without this discipline, or something equally strong, there is a risk of projection of anthropomorphic semiotic terminology onto unsuitable hosts, leading, if unchecked, to the sort of animism that biology in particular has only recently escaped. The problem is suspect whenever teleological notions are used outside of mental or social contexts.1 Although our animistic ancestors may have had a closer rapport with Nature than modern scientists, contemporary scientific explanation requires an understanding of causal structure (Salmon 1984). On the other hand, unless the causal rendition of semiosis can capture full blown cognitive semiosis, it is likely to be too restrictive for the evaluation of primal semiosis in general

Emergence has traditionally been described as satisfying specific properties, notably nonreducibility of the emergent object or properties to their substrate, novelty, and unpredictability from the properties of the substrate. Sometimes more mysterious properties such as independence from the substrate, separate substances and teleological properties are invoked. I will argue that the latter are both unnecessary and unwarranted. The descriptive properties can be analyzed in more detail in logical terms, but the logical conditions alone do not tell us how to identify the conditions through interactions with the world. In order to do that we need dynamical properties – properties that do something. This paper, then, will be directed at identifying the dynamical conditions necessary and sufficient for emergence. Emergent properties and objects all result or are maintained by dissipative and radically nonholonomic processes. Emergent properties are relatively common in physics, but have been ignored because of the predominant use of Hamiltonian methods assuming energy conservation. Emergent objects are all dissipative systems, which have been recognized as special only in the past fifty years or so. Of interest are autonomous systems, including living and thinking systems. They show functionality and are self governed

Almost fifty years ago Wilfrid Sellars described two competing ways of imagining the world, the Manifest Image and the Scientific Image. The Manifest Image is an idealization of common sense aided by critical philosophy, whereas the Scientific Image is the product of our best science. The methodologies of the two images are very different: the Manifest Image deals with experience and looks only at relations among bits of experience and analysis of experience into the relations that must lie behind it, whereas the Scientific Image is grounded in explanations of experience, typically causal explanations. This need not be a problem if the two images are compatible. Sellars argued, however, that the Manifest Image implies continuity, but the best science of the time told us that the world is made up of discrete subatomic particles and discrete transitions between quantum states, making the two incompatible. Although Sellars noted that future science might show that the world is continuous, he did not follow this up. Science in the last fifty years has given much more evidence for continuity in the world from complexity studies and Quantum Mechanics, so perhaps the two images can be reconciled after all

The paradigm of Laplacean determinism combines three regulative principles: determinism, predictability, and the explanatory adequacy of universal laws together with purely local conditions. Historically, it applied to celestial mechanics, but it has been expanded into an ideal for scientific theories whose cogency is often not questioned. Laplace’s demon is an idealization of mechanistic scientific method. Its principles together imply reducibility, and rule out holism and emergence. I will argue that Laplacean determinism fails even in the realm of planetary dynamics, and that it does not give suitable criteria for explanatory success except within very well defined and rather exceptional domains. Ironically, the very successes of Laplacean method in the Solar System were made possible only by processes that are not themselves tractable to Laplacean methodology. The results of some of these processes were first observed in 1964, and violate the Lapacean requirements of locality and predictability, opening the door to holism and nonreducibility, i.e., emergence. Despite the falsification of Laplacean methodology, the explanatory resources of holism and emergence remain in scientific limbo, though emergence has been used somewhat indiscriminately in recent scientific literature. I make some remarks at the end about the proper use of emergence in its traditional sense going back to C.D. Broad

Against standard approaches to evolution and ethics, this book develops the idea that moral values may find their origin in regularly recurring features in the cooperative environments of species of organisms that are social and intelligent. Across a wide range of species that are social and intelligent, possibilities arise for helping others, responding empathetically to the needs of others, and playing fairly. The book identifies these underlying environmental regularities as biological natural kinds and as natural moral values. As natural kinds, moral values help to provide more complete explanations for the selection of traits that arise in response to them. For example, helping in an aquatic environment is quite different than helping in an arboreal environment, and so we can expect the selection of traits for helping to reflect these underlying environmental differences. With the human ability to name, talk, and reason about important features of our environment, moral values become part of moral discourse and argument, helping to produce coherent systems of moral thought. Combining a naturalistic approach to morality with an equal emphasis on moral argument and truth, this book will be of interest to philosophers and historians of biology, theoretical biologists, comparative psychologists, and moral philosophers.

A system is autonomous if it uses its own information to modify itself and its environment to enhance its survival, responding to both environmental and internal stimuli to modify its basic functions to increase its viability. Autonomy is the foundation of functionality, intentionality and meaning. Autonomous systems accommodate the unexpected through self-organizing processes, together with some constraints that maintain autonomy. Early versions of autonomy, such as autopoiesis and closure to efficient cause, made autonomous systems dynamically closed to information. This contrasts with recent work on open systems and information dynamics. On our account, autonomy is a matter of degree depending on the relative organization of the system and system environment interactions. A choice between third person openness and first person closure is not required.

Kuhn's incommensurability thesis has generally been interpreted by friends and foes alike so as to preclude direct rational communication across revolutionary divides in science. In this paper, a weaker form of incommensurability is sketched which allows eventual comparison of incommensurable theories, but is consistent with Kuhn's model of science. Incommensurability occurs whenever the knowledge or ability to translate from the language of one theory to that of another is lacking. It can be resolved by acquiring the necessary knowledge or ability.

Goodman’s account of the ‘grue’ paradox stands at a crossroads in the history of twentieth century epistemology. Published in 1954, Fact, Fiction, and Forecast is a reaction to the logical empiricist views that held sway in the first half of the last century and anticipates many of the conventionalist and/or relativist moves popular throughout the second half. Through his evaluation of Hume’s problem of induction, as well as his own novel reformulation of it, Goodman comes to reject a number of the fundamental parts of logical empiricism. In particular, Goodman argues that the formal epistemic methods the logical empiricists wanted to rely upon are insufficient. This leads him to turn towards conventionalism, which is the basis of his rejection of the objective view of knowledge. In his conventionalism he is a precursor of writers such as Hanson, Kuhn and Feyerabend, who, seeing the inadequacy of formalism, sought to fill the gaps it left in epistemic methodology with scientific values, tacit knowledge and linguistic practices. Making use of Susan Haack’s distinction between three different kinds of foundationalism, we analyse Goodman’s position and its relation to the views of the logical empiricists. The two are reflections of each other in that, where the logical empiricists are foundationalists in their views on empirical evidence, methods used and objective criteria of justification, Goodman consistently opts for the corresponding coherentist options. As it turns out, this choice of options makes it impossible for Goodman to deal with the very objections he raises against the logical empiricists. In adding the new problem of induction to the old one, Goodman adds a problem which clearly can not be resolved by a purely syntactic solution. The charge Goodman raises is that logical empiricists cannot determine which predictions are sound and which are not. We argue that his method of identifying acceptable predictions based on the use of entrenchment is, in the end, arbitrary and only postpones the underlying problem.

Wilfrid Sellars described his Manifest Image and Scientific Image as idealizations of our common sense and scientific views of the world, including our own special role in the world as humans. If, as Sellars suggested, there is an irreconcilable conflict between these images, it may not be possible to reconcile science with common sense. The Scientific Image, as we have inherited it, has a strong reductionist element that seems to imply that things are not really as they appear to common sense. Although some amount of discrepancy between common sense and science is not a problem, since we know from experience that we may be mistaken about nearly any given thing, a systematic clash between science and common sense presents problems for the acceptance of one, the other, or both views

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.

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