The importance of the observer in science

The concept of {\em complexity} (as a quantity) has been plagued by numerous contradictory and confusing definitions. By explicitly recognising a role for the observer of a system, an observer that attaches meaning to data about the system, these contradictions can be resolved, and the numerous complexity measures that have been proposed can be seen as cases where different observers are relevant, and/or being proxy measures that loosely scale with complexity, but are easy to compute from the available data. Much of the epistemic confusion in the subject can be squarely placed at science's tradition of removing the observer from the description in order to guarantee {\em objectivity}. Explicitly acknowledging the role of the observer helps untangle other confused subject areas. {\em Emergence} is a topic about which much ink has been spilt, but it can be understand easily as an irreducibility between description space and meaning space. Quantum Mechanics can also be understood as a theory of observation. The success in explaining quantum mechanics, leads one to conjecture that all of physics may be reducible to properties of the observer. And indeed, what are the necessary (as opposed to contingent) properties of an observer? This requires a full theory of consciousness, from which we are a long way from obtaining. However where progress does appear to have been made, e.g. Daniel Dennett's {\em Consciousness Explained}, a recurring theme of self-observation is a crucial ingredient.Comment: In Proceedings The Two Cultures: Reconsidering the division between the Sciences and Humanities, UNSW, July 200

Networks: open, closed or complex. Connecting philosophy, design and innovation, part 3

This is the third and final paper of a series bringing a philosophical investigation to matters of design and innovation. With the others examining: first, the urges to reconsider innovation from a creative, specifically design, direction (‘Beyond Success’); and second, the type of dynamic innovation that may be thus reconsidered (‘Ecstatic Innovation’); this paper will investigate a way of constructing this type of design-driven innovation. It will begin by looking at the networks that can be created to deliver a dynamic, continually innovative innovation and will start by considering two concepts of network: the open and the closed. While there seems to be an easy distinction to be made between open and closed, and its mapping onto similarly convenient ideas of good and bad, I hope to show that this is not the case. The complexity of networked forms of organisation demand that we bring to them a complexity of thought that comes from philosophy. Nevertheless, such an account will also need to engage with discourses from other disciplinary areas: notably organisational theory, innovation management and design. The outcome is of importance to thinking the organisational structures in which innovation is managed

The Computability-Theoretic Content of Emergence

In dealing with emergent phenomena, a common task is to identify useful descriptions of them in terms of the underlying atomic processes, and to extract enough computational content from these descriptions to enable predictions to be made. Generally, the underlying atomic processes are quite well understood, and (with important exceptions) captured by mathematics from which it is relatively easy to extract algorithmic con- tent. A widespread view is that the difficulty in describing transitions from algorithmic activity to the emergence associated with chaotic situations is a simple case of complexity outstripping computational resources and human ingenuity. Or, on the other hand, that phenomena transcending the standard Turing model of computation, if they exist, must necessarily lie outside the domain of classical computability theory. In this article we suggest that much of the current confusion arises from conceptual gaps and the lack of a suitably fundamental model within which to situate emergence. We examine the potential for placing emer- gent relations in a familiar context based on Turing's 1939 model for interactive computation over structures described in terms of reals. The explanatory power of this model is explored, formalising informal descrip- tions in terms of mathematical definability and invariance, and relating a range of basic scientific puzzles to results and intractable problems in computability theory

Epistemic virtues, metavirtues, and computational complexity

I argue that considerations about computational complexity show that all finite agents need characteristics like those that have been called epistemic virtues. The necessity of these virtues follows in part from the nonexistence of shortcuts, or efficient ways of finding shortcuts, to cognitively expensive routines. It follows that agents must possess the capacities – metavirtues –of developing in advance the cognitive virtues they will need when time and memory are at a premium

Layout Planning with Isles: A Genetic Approach

Plant layout problems involve distributing different resources or departments in a given plant and achieving maximum efficiency for the services or goods being made or offered. To this end, plants are designed to optimize production flow from the first stage (i.e. as raw material) to finish product. However, optimization which is generally expressed either in terms of minimization (for example, of material handling costs) or of maximization (for example, the number of desired adjacencies in a qualitative chart) is not always feasible when real problems or real sizes are being handled. The level of complexity may turn out considerable as the number of parameters, restrictions and other variables considered in the study become larger. This kind of problem has been formulated, from a mathematical view point as a static quadratic assignment problem. However, the number of problems that are usceptible to being solved by optimization methods is very limited. Some alternatives have been called from the field of graph-theory, direct method algorithms, construction algorithms (such as CORELAP), and improvement algorithms (such as CRAFT). In this thesis work, an attempt is made to develop the algorithm for solving layout problem with real-life restriction like aisles, used in factories for the easy transfer of materials from one section to the other, using Genetic Algorithm

A Computable Economist’s Perspective on Computational Complexity

A computable economist's view of the world of computational complexity theory is described. This means the model of computation underpinning theories of computational complexity plays a central role. The emergence of computational complexity theories from diverse traditions is emphasised. The unifications that emerged in the modern era was codified by means of the notions of efficiency of computations, non-deterministic computations, completeness, reducibility and verifiability - all three of the latter concepts had their origins on what may be called 'Post's Program of Research for Higher Recursion Theory'. Approximations, computations and constructions are also emphasised. The recent real model of computation as a basis for studying computational complexity in the domain of the reals is also presented and discussed, albeit critically. A brief sceptical section on algorithmic complexity theory is included in an appendix