The drastically increasing availability ofmodern computers coupled with the equally drasticallylower cost of a given amount of computer power inrecent years has resulted in the evolution of thetraditional experimental/theoretical dichotomy inchemistry into anexperimental/theoretical/computational trichotomy. This trichotomy can be schematically represented by atriangle with experimental,theoretical, and computational chemistry at the threevertices. The ET and EC edges of the ETC triangledepict the uses of theoretical and computationalchemistry, respectively, to predict and interpretexperimental results. The TC edge (...) depicts therelationship between theoretical and computationalchemistry. Mathematics plays an increasing role in allaspects of chemistry, particularly theoreticalchemistry, and has led to the evolution of thediscipline of mathematical chemistry. Research inmathematical chemistry can be considered to lie on achemistry-mathematics continuum depending on therelative depths of the underlying chemistry andmathematics. Examples of the author's own researchlying near each end of the chemistry-mathematicscontinuum include his work on applications of graphtheory and topology in inorganic coordination andcluster chemistry lying near the chemistry end and hiswork on chirality algebra lying near the mathematicsend. The general points in this essay are illustratedby an analysis of the roles of computational andtheoretical chemistry in developing an understandingof structure and bonding in deltahedral boranes andrelated carboranes. This work has allowed extensionof the concept of aromaticity from two dimensions asin benzene and other planar hydrocarbons to the thirddimension in deltahedral boranes. (shrink)

This book reflects on the significant and highly original scientific contributions of Hans Primas. A professor of chemistry at ETH Zurich from 1962 to 1995, Primas continued his research activities until his death in 2014. Over these 50 years and more, he worked on the foundations of nuclear magnetic resonance spectroscopy, contributed to a number of significant issues in theoretical chemistry, helped to clarify central topics in quantum theory and the philosophy of physics, suggested innovative ways of (...) addressing interlevel relations in the philosophy of science, and introduced cutting-edge approaches in the flourishing young field of scientific studies of consciousness. His work in these areas of research and its continuing impact is described by noted experts, colleagues, and collaborators of Primas. All authors contextualize their contributions to facilitate the mutual dialog between these fields. (shrink)

Usually within the context of computer simulations in quantum chemistry practices, there is a distinction between ab initio and semi-empirical methods. Related to this, a controversy within the scientific and philosophical communities came about regarding the superiority of the ab initio methods due to their theoretical rigor. In this article we re-evaluate the condition of the semi-empirical simulations in this area of research. We examine some of the aspects of this debate that have been considered in philosophy and (...) provide additional elements to the analysis. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the (...) nature of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

Molecules have more or less symmetric and complex structures which can be defined in the mathematical framework of topology, group theory, dynamical systems theory, and quantum mechanics. But symmetry and complexity are by no means only theoretical concepts of research. Modern computer aided visualizations show real forms of matter which nevertheless depend on the technical standards of observation, computation, and representation. Furthermore, symmetry and complexity are fundamental interdisciplinary concepts of research inspiring the natural sciences since the antiquity.

Polysemy is a term used in semantic and lexical analysis to describe a word with multiple meanings. Although such words present few difficulties in everyday communication, they do pose near-intractable problems for linguists and lexicographers. The contributors in this volume consider the implications of these problems for linguistic theory and how they may be addressed in computational linguistics.

The ideas of quantum simulation and advances in quantum algorithms to solve quantum chemistry problems have been discussed. Theoretical proposals and experimental investigations both have been studied to gauge the extent to which quantum computation has been applied to solve quantum chemical problems till date. The distinctive features and limitations of the application of quantum simulation on chemical systems and current approaches to define and improve upon standard quantum algorithms have been studied in detail. The possibility and consequences (...) of designing an efficient quantum computer that can address chemical problems have been assessed. The experimental realization of quantum supremacy defies the conventional belief of chemists, that millions of qubits would be required to solve fundamental chemistry problems. It is predicted that quantum simulation of quantum chemistry problems will radically revolutionize this field. (shrink)

Algorithmic chemistries are often based on a fixed formalism which limits the fragment of chemistry expressible in the domain of the models. This results in limited applicability of the models in contemporary mathematical chemistry and is due to the poor fit between the logic used for model construction and the system being modeled. In this paper, I propose a system-oriented methodology which selects a formalism through a mapping of chemical transformation rules to proof-theoretic structural rules. Using a formal (...) specification framework from the field of artificial chemistry, expressive adequacy is ensured by the choice of logic being based on the system properties to be modeled. To illustrate the methodology, a case study is provided that shows how the proposed approach selects linear logic for modeling resource sensitivity and the proof-theoretic interpretation facilitates translation to a programming language. Since the method results in a plurality of models, I conclude with a discussion on how the proposal contributes to multi-model paradigms in computational pharmacology. (shrink)

This book addresses a wide range of topics relating to the properties and behavior of condensed matter under extreme conditions such as intense magnetic and electric fields, high pressures, heat and cold, and mechanical stresses. It is divided into four sections devoted to condensed matter theory, molecular chemistry, theoretical physics, and the philosophy and history of science. The main themes include electronic correlations in material systems under extreme pressure and temperature conditions, surface physics, the transport properties of low-dimensional (...) electronic systems, applications of the density functional theory in molecular systems, and graphene. The book is the outcome of a workshop held at the University of Catania, Italy, in honor of Professor Renato Pucci on the occasion of his 70th birthday. It includes selected invited contributions from collaborators and co-authors of Professor Pucci during his long and successful career, as well as from other distinguished guest authors. (shrink)

The aim of this book is to show how supramolecular complexity of cell organization can dramatically alter the functions of individual macromolecules within a cell. The emergence of new functions which appear as a consequence of supramolecular complexity, is explained in terms of physical chemistry. The book is interdisciplinary, at the border between cell biochemistry, physics and physical chemistry. This interdisciplinarity does not result in the use of physical techniques but from the use of physical concepts to study (...) biological problems. In the domain of complexity studies, most works are purely theoretical or based on computer simulation. The present book is partly theoretical, partly experimental and theory is always based on experimental results. Moreover, the book encompasses in a unified manner the dynamic aspects of many different biological fields ranging from dynamics to pattern emergence in a young embryo. The volume puts emphasis on dynamic physical studies of biological events. It also develops, in a unified perspective, this new interdisciplinary approach of various important problems of cell biology and chemistry, ranging from enzyme dynamics to pattern formation during embryo development, thus paving the way to what may become a central issue of future biology. (shrink)

A personal account is presented for the present status of mathematical chemistry, with emphasis on non-numerical applications. These use mainly graph-theoretical concepts. Most computational chemical applications involve quantum chemistry and are therefore largely reducible to physics, while discrete mathematical applications often do not. A survey is provided for opinions and definitions of mathematical chemistry, and then for journals, books and book series, as well as symposia of mathematical chemistry.

Traditional philosophy of science regards theoretical reasoning, based on the example of Euclidian geometry, as the hallmark of a mature science. There is, however, a parallel tradition of practical reasoning based on specific cases that goes back to Aristotle. In this paper I argue that practical reasoning is an essential part of the practice of chemistry and should be understood and appreciated on its own merits rather than regarded as a symbol of the immaturity and inferiority of (...) class='Hi'>chemistry as a science. (shrink)

. Computational chemistry grew in a new era of “desktop modeling,” which coincided with a growing demand for modeling software, especially from the pharmaceutical industry. Parameterization of models in computational chemistry is an arduous enterprise, and we argue that this activity leads, in this specific context, to tensions among scientists regarding the epistemic opacity transparency of parameterized methods and the software implementing them. We relate one flame war from the Computational Chemistry mailing List in (...) order to assess in detail the relationships between modeling methods, parameterization, software and the various forms of their enclosure or disclosure. Our claim is that parameterization issues are an important and often neglected source of epistemic opacity and that this opacity is entangled in methods and software alike. Models and software must be addressed together to understand the epistemological tensions at stake. (shrink)

In this paper we investigate with a case study from chemistry under what conditions a simulation can serve as a surrogate for an experiment. The case-study concerns a simulation of H2-formation in outer space. We find that in this case the simulation can act as a surrogate for an experiment, because there exists comprehensive theoretical background knowledge in form of quantum mechanics about the range of phenomena to which the investigated process belongs and because any particular modelling assumptions (...) as can be justified. If these requirements are met then direct empirical validation may even be dispensable. We conjecture that this is not the case in the absence of comprehensive theoretical background knowledge. (shrink)

This volume contains the proceedings of three special sessions: Algebra and Computer Science, held during the Joint AMS-EMS-SPM meeting in Porto, Portugal, June 10–13, 2015; Groups, Algorithms, and Cryptography, held during the Joint Mathematics Meeting in San Antonio, TX, January 10–13, 2015; and Applications of Algebra to Cryptography, held during the Joint AMS-Israel Mathematical Union meeting in Tel-Aviv, Israel, June 16–19, 2014. Papers contained in this volume address a wide range of topics, from theoretical aspects of algebra, namely group (...) theory, universal algebra and related areas, to applications in several different areas of computer science. From the computational side, the book aims to reflect the rapidly emerging area of algorithmic problems in algebra, their computational complexity and applications, including information security, constraint satisfaction problems, and decision theory. The book gives special attention to recent advances in quantum computing that highlight the need for a variety of new intractability assumptions and have resulted in a new area called group-based cryptography. (shrink)

The paper is focused on some aspects of experimental realism of Ian Hacking, and especially on his manipulability criterion of existence. The problem is here related to chemical molecules, the objects of interest in chemical research. The authors consider whether and to what extent this criterion has been applied in experimental practice of chemistry. They argue that experimentation on is a fundamental criterion of existence of entities in chemistry rather than experimentation with. Some examples regarding studies of structures (...) of complex compounds, taken from organic chemistry, are presented to support the authors' considerations. Chemists' laboratory practice depends strongly on the way that representations of entities on (or with) the experiments are used. The authors show that this point has not been given sufficient attention by the new experimentalists. (shrink)

The result of the author's extensive practical experience: a decade in computer process control using large scale systems, another decade in machine pattern-recognition for vision systems, and nearly a decade dealing with artificial intelligence and expert systems. These real-life projects have taught Vámos a critical appreciation of, and respect for, both abstract theory and the practical methodology that grows out of—and, in turn, shapes—those theories.Machine representation means a level of formalization that can be expressed by the instruments of mathematics, whereas (...) programming is not more and not less than a special linguistic translation of these mathematical formulae. How these all are related and controlled is a most practical philosophical and computation professional task. Wide experience in the practical fields of computer science, and the research of the underlying theoretical issues have led Vámos to the development of the attitude and activity of constructive skepticism. (shrink)

The book presents investigations into the world of info-computational nature, in which information constitutes the structure, while computational process amounts to its change. Information and computation are inextricably bound: There is no computation without informational structure, and there is no information without computational process. Those two complementary ideas are used to build a conceptual net, which according to Novalis is a theoretical way of capturing reality. We apprehend the reality within a framework known as natural computationalism, (...) the view that the whole universe can be understood as a computational system at many different levels - from quantum mechanical world, to biological organisms including intelligent minds and their societies. Questions about nature of information and computation and their unified view are addressed along with application of info- computational approach to knowledge generation. (shrink)

Molecular models are typical topics of chemical research depending on the technical standards of observation, computation, and representation. Mathematically, molecular structures have been represented by means of graph theory, topology, differential equations, and numerical procedures. With the increasing capabilities of computer networks, computational models and computer-assisted visualization become an essential part of chemical research. Object-oriented programming languages create a virtual reality of chemical structures opening new avenues of exploration and collaboration in chemistry. From an epistemic point of view, (...) virtual reality is a new computer-assisted tool of human imagination and recognition. (shrink)

The systems view on life and its emergence from complex chemistry has remarkably increased the scientific attention on metabolism in the last two decades. However, during this time there has not been much theoretical discussion on what constitutes a metabolism and what role it actually played in biogenesis. A critical and updated review on the topic is here offered, including some references to classical models from last century, but focusing more on current and future research. Metabolism is considered (...) as intrinsically related to the living but not necessarily equivalent to it. More precisely, the idea of “minimal metabolism”, in contrast to previous, top‐down conceptions, is formulated as a heuristic construct, halfway between chemistry and biology. Thus, rather than providing a complete or final characterization of metabolism, our aim is to encourage further investigations on it, particularly in the context of life's origin, for which some concrete methodological suggestions are provided. Also see the video abstract here:https://youtu.be/DP7VMKk2qpA. (shrink)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more fact-oriented (...) and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

Computationalism holds that our grasp of notions like ‘computable function’ can be used to account for our putative ability to refer to the standard model of arithmetic. Tennenbaum's Theorem has been repeatedly invoked in service of this claim. I will argue that not only do the relevant class of arguments fail, but that the result itself is most naturally understood as having the opposite of a reference-fixing effect — i.e., rather than securing the determinacy of number-theoretic reference, Tennenbaum's Theorem points (...) towards a sense in which portions of our computational vocabulary should be regarded as model-relative. (shrink)

A collection of scholarly essays, __Complexity Theory and the Philosophy of Education__ provides an accessible theoretical introduction to the topic of complexity theory while considering its broader implications for educational change. Explains the contributions of complexity theory to philosophy of education, curriculum, and educational research Brings together new research by an international team of contributors Debates issues ranging from the culture of curriculum, to the implications of work of key philosophers such as Foucault and John Dewey for educational change (...) Demonstrates how social scientists and social and education policy makers are drawing on complexity theory to answer questions such as: why is it that education decision-makers are so resistant to change; how does change in education happen; and what does it take to make these changes sustainable? Considers changes in use of complexity theory; developed principally in the fields of physics, biology, chemistry, and economics, and now being applied more broadly to the social sciences and to the study of education. (shrink)

The book starts with the assumption that vagueness is a fundamental property of this world. From a philosophical account of vagueness via the presentation of alternative mathematics of vagueness, the subsequent chapters explore how vagueness manifests itself in the various exact sciences: physics, chemistry, biology, medicine, computer science, and engineering.

We show that there is a structure of countably infinite signature with $P = N_{2}P$ and a structure of finite signature with $P = N_{1}P$ and $N_{1}P \neq N_{2}P$ . We give a further example of a structure of finite signature with $P \neq N_{1}P$ and $N_{1}P \neq N_{2}P$ . Together with a result from [10] this implies that for each possibility of P versus NP over structures there is an example of countably infinite signature. Then we show that for (...) some finite ℒ the class of ℒ-structures with $P = N_{1}P$ is not closed under ultraproducts and obtain as corollaries that this class is not $\delta$ -elementary and that the class of ᵍ-structures with $P \neq N_{1}P$ is not elementary. Finally we prove that for all f dominating all polynomials there is a structure of finite signature with the following properties: $P \neq N_{1}P$ . $N_{1}P \neq N_{2}P$ , the levels $N_{2}TIME(n^{i})$ of $N_{2}P$ and the levels $N_{1}TIME(n^{i})$ of $N_{1}P$ are different for different i, indeed $DTIME(n^{i'}) \nsubseteq N_{2}TIME(n^{i})$ if $i' \textgreater i$ ; $DTIME(f) \nsubseteq N_{2}P$ , and $N_{2}P \nsubseteq DEC$ . DEC is the class of recognizable sets with recognizable complements. So this is an example where the internal structure of $N_{2}P$ is analyzed in a more detailed way. In our proofs we use methods in the style of classical computability theory to construct structures except for one use of ultraproducts. (shrink)

This volume is the first systematic and thorough attempt to investigate the relation and the possible applications of mereology to contemporary science. It gathers contributions from leading scholars in the field and covers a wide range of scientific theories and practices such as physics, mathematics, chemistry, biology, computer science and engineering. Throughout the volume, a variety of foundational issues are investigated both from the formal and the empirical point of view. The first section looks at the topic as it (...) applies to physics. The section addresses questions of persistence and composition within quantum and relativistic physics and concludes by scrutinizing the possibility to capture continuity of motion as described by our best physical theories within gunky space times. The second part tackles mathematics and shows how to provide a foundation for point-free geometry of space switching to fuzzy-logic. The relation between mereological sums and set-theoretic suprema is investigated and issues about different mereological perspectives such as classical and natural Mereology are thoroughly discussed. The third section in the volume looks at natural science. Several questions from biology, medicine and chemistry are investigated. From the perspective of biology, there is an attempt to provide axioms for inferring statements about part hood between two biological entities from statements about their spatial relation. From the perspective of chemistry, it is argued that classical mereological frameworks are not adequate to capture the practices of chemistry in that they consider neither temporal nor modal parameters. The final part introduces computer science and engineering. A new formal mereological framework in which an indeterminate relation of part hood is taken as a primitive notion is constructed and then applied to a wide variety of disciplines from robotics to knowledge engineering. A formal framework for discrete mereotopology and its applications is developed and finally, the importance of mereology for the relatively new science of domain engineering is also discussed. (shrink)

Epistemologists have debated at length whether scientific discovery is a rational and logical process. If it is, according to the Artificial Intelligence hypothesis, it should be possible to write computer programs able to discover laws or theories; and if such programs were written, this would definitely prove the existence of a logic of discovery. Attempts in this direction, however, have been unsuccessful: the programs written by Simon's group, indeed, infer famous laws of physics and chemistry; but having found no (...) new law, they cannot properly be considered discovery machines. The programs written in the Turing tradition, instead, produced new and useful empirical generalization, but no theoretical discovery, thus failing to prove the logical character of the most significant kind of discoveries. A new cognitivist and connectionist approach by Holland, Holyoak, Nisbett and Thagard, looks more promising. Reflection on their proposals helps to understand the complex character of discovery processes, the abandonment of belief in the logic of discovery by logical positivists, and the necessity of a realist interpretation of scientific research. (shrink)

Ranging from Alan Turing’s seminal 1936 paper to the latest work on Kolmogorov complexity and linear logic, this comprehensive new work clarifies the relationship between computability on the one hand and constructivity on the other. The authors argue that even though constructivists have largely shed Brouwer’s solipsistic attitude to logic, there remain points of disagreement to this day. Focusing on the growing pains computability experienced as it was forced to address the demands of rapidly expanding applications, the content maps the (...) developments following Turing’s ground-breaking linkage of computation and the machine, the resulting birth of complexity theory, the innovations of Kolmogorov complexity and resolving the dissonances between proof theoretical semantics and canonical proof feasibility. Finally, it explores one of the most fundamental questions concerning the interface between constructivity and computability: whether the theory of recursive functions is needed for a rigorous development of constructive mathematics. This volume contributes to the unity of science by overcoming disunities rather than offering an overarching framework. It posits that computability’s adoption of a classical, ontological point of view kept these imperatives separated. In studying the relationship between the two, it is a vital step forward in overcoming the disagreements and misunderstandings which stand in the way of a unifying view of logic. (shrink)

This article explores a new form of epistemic injustice related to computers and data mining in our interconnected world. I argue that data mining, as it is currently practiced, not only perpetuates but also contributes to a moral injustice primarily driven by economic factors. By employing Gaile Pohlhaus’s theoretical framework, the paper establishes criteria that classify data mining as a form of epistemic injustice (P1) and demonstrates its differentiation from other known forms in existing literature (P2). Through a comprehensive (...) analysis of data mining’s alignment with these criteria, the article highlights its unique nature and draws attention to its previously overlooked manifestation of epistemic injustice. By comparing data mining to established forms of epistemic injustice, this research underscores the urgent need for a critical examination of this ethical dilemma arising from technological advancements. (shrink)

Mathematics is about proofs, that is the derivation of correct statements; and calculations, that is the production of results according to well-defined sets of rules. The two notions are intimately related. Proofs can involve calculations, and the algorithm underlying a calculation should be proved correct. The aim of the author is to explore this relationship. The book itself forms an introduction to simple type theory. Starting from the familiar propositional calculus the author develops the central idea of an applied lambda-calculus. (...) This is illustrated by an account of Gödel's T, a system which codifies number-theoretic function hierarchies. Each of the book's 52 sections ends with a set of exercises, some 200 in total. These are designed to help the reader get to grips with the subject, and develop a further understanding. An appendix contains complete solutions of these exercises. (shrink)

This paper discusses how computational modeling combines the autonomy of models with the automation of computational procedures. In particular, the case of ab-initio methods in quantum chemistry will be investigated to draw two lessons from the analysis of computational modeling. The first belongs to general philosophy of science: Computational modeling faces a trade-off and enlarges predictive force at the cost of explanatory force. The other lesson is about the philosophy of chemistry: The methodology of (...) computational modeling puts into doubt claims about the reduction of chemistry to physics. (shrink)

This much-needed book provides a thorough account of temporal logic, one of the most important areas of logic in computer science today. The book begins with a solid introduction to semantical and axiomatic approaches to temporal logic. It goes on to cover predicate temporal logic, meta-languages, general theories of axiomatization, many dimensional systems, propositional quantifiers, expressive power, Henkin dimension, temporalization of other logics, and decidability results. With its inclusion of cutting-edge results and unifying methodologies, this book is an indispensable reference (...) for both the pure logician and the theoretical computer scientist. (shrink)

Any discussion of the concept of “formal science” must acknowledge that the term is used in different ways, for different purposes, by different people. For some, the formal sciences are defined by the exclusive use of deductive methods for discovering, or reasoning about, the properties of formal, abstract systems. On this view, the formal sciences are synonymous with mathematics, formal logic, and certain branches of linguistics and computer science that emphasize the study of formal languages. For others, “formal science” means (...) something like “exact science”, or “formalized science”. On this view, any scientific discipline that places heavy emphasis on mathematical or logical formalization of key theoretical concepts and theories, could be described as a formal science. This latter conception of formal science is much more liberal than the former, and would include all of physics, much of chemistry, and some parts of biology, ecology, psychology and economics, as well as newer computationoriented disciplines like artificial life and artificial intelligence that do not fit easily within the traditional classification of the sciences. (shrink)

Collecting, comparing, and computing molecular sequences are among the most prevalent practices in contemporary biological research. They represent a specific way of producing knowledge. This paper explores the historical development of these practices, focusing on the work of Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley, who produced the first computer-based collection of protein sequences, published in book format in 1965 as the Atlas of Protein Sequence and Structure. While these practices are generally associated with the rise of (...) molecular evolution in the 1960s, this paper shows that they grew out of research agendas from the previous decade, including the biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code. It also shows how computers became essential for the handling and analysis of sequence data. Finally, this paper reflects on the relationships between experimenting and collecting as two distinct “ways of knowing” that were essential for the transformation of the life sciences in the twentieth century. (shrink)

Attempts to lay a foundation for the sciences based on modern mathematics are questioned. In particular, it is not clear that computer science should be based on set-theoretic mathematics. Set-theoretic mathematics has difficulties with its own foundations, making it reasonable to explore alternative foundations for the sciences. The role of computation within an alternative framework may prove to be of great potential in establishing a direction for the new field of computer science.Whitehead''s theory of reality is re-examined as a foundation (...) for the sciences. His theory does not simply attempt to add formal rigor to the sciences, but instead relies on the methods of the biological and social sciences to construct his world-view. Whitehead''s theory is a rich source of notions that are intended to explain every element of experience. It is a product of Whitehead''s earlier attempt to provide a mathematical foundation for the physical sciences and is still consistent with modern physics. (shrink)

Computational philosophy (CP) aims at investigating many important concepts and problems of the philosophical and epistemological tradition in a new way by taking advantage of information-theoretic, cognitive, and artificial intelligence methodologies. I maintain that the results of computational philosophy meet the classical requirements of some Peircian pragmatic ambitions. Indeed, more than a 100 years ago, the American philosopher C.S. Peirce, when working on logical and philosophical problems, suggested the concept of pragmatism(pragmaticism, in his own words) as a logical (...) criterion to analyze what words and concepts express through their practical meaning. Many words have been spent on creative processes and reasoning, especially in the case of scientific practices. In fact, many philosophers have usually offered a number of ways of construing hypotheses generation, but they aim at demonstrating that the activity of generating hypotheses is paradoxical, obscure, and thus not analyzable. Those descriptions are often so far from Peircian pragmatic prescription and so abstract to result completely unknowable and obscure. To dismiss this tendency and gain interesting insight about the so-called logic of scientific discovery we need to build constructive procedures, which could play a role in moving the problem-solving process forward by implementing them in some actual models. The computational turn gives us a new way to understand creative processes in a strictly pragmatic sense. In fact, by exploiting artificial intelligence and cognitive science tools, computational philosophy allows us to test concepts and ideas previously conceived only in abstract terms. It is in the perspective of these actual computational models that I find the central role of abduction in the explanation of creative reasoning in science. I maintain that the computational philosophy analysis of model-based and manipulative abduction and of external and epistemic mediators is important not only to delineate the actual practice of abduction, but also to further enhance the development of programs computationally adequate in rediscovering, or discovering for the first time, for example, scientific hypotheses or mathematical theorems. The last part of the paper is devoted to illustrating the problem of the extra-theoretical dimension of reasoning and discovery from the perspective of some mathematical cases derived from calculus and geometry. (shrink)

This paper reviews the relatively small body of work in computer ethics which looks at the question of whether gender makes any difference to ethical decisions. There are two strands of writing on gender and computer ethics. The first focuses on problems of women's access to computer technology; the second concentrates on whether there are differences between men and women's ethical decision making in relation to information and computing technologies. I criticize the latter area, arguing that such studies survey student (...) audiences, that they emphasize the result of an ethical decision over the process of arriving at the decision, that they are problematic in relation to research methodology and that they are undertheorized. Given that traditional ethical theories largely ignore gender, I offer a gender based ethics in terms of feminist ethics as the best place to look for theoretical substance. The paper concludes by considering how feminist ethics can be combined with empirical studies that emphasize observation and interviewing in order to move gender and computer ethics onward from statistical studies of men's and women's ethical decisions toward more substantially theorized studies of areas in computer ethics which have gender implications, such as privacy and power. (shrink)

If we are to understand the nature of science, we must see it as an activity and achievement of the human mind alongside others, such as the achievements of children in learning to talk and to cope with people and other objects in their environment, and the achievements of non-scientists living in a rich and complex world which constantly poses problems to be solved. Looking at scientific knowledge as one form of human knowledge, scientific understanding as one form of human (...) understanding, scientific investigation as one form of human problem-solving activity, we can begin to see more clearly what science is, and also what kind of mechanism the human mind is. -/- By undermining the slogan that science is the search for laws, and subsidiary slogans such as that quantification is essential, that scientific theories must be empirically refutable, and that the methods of philosophers cannot serve the aims of scientists, I shall try, in what follows, to liberate some scientists from the dogmas indoctrinated in universities and colleges. I shall also try to show philosophers how they can contribute to the scientific study of man, thereby escaping from the barrenness and triviality complained of so often by non-philosophers and philosophy students. -/- A side-effect which will be reported elsewhere, is to undermine some old philosophical distinctions and pour cold water on battles which rage around them -- like the distinction between subjectivity and objectivity, and the battles between empiricists and rationalists. -/- Key idea: A major aim of science is not to discover and explain laws, but to discover what is possible, and how it is possible. -/- This view of science developed further in Sloman (1978) helps to explain the contributions of Theoretical Linguistics, Chemistry, Artificial Intelligence, and Computer Science insofar as they all enrich our understanding of what is possible and how it is possible. -/- Download: http://www.cs.bham.ac.uk/research/projects/cogaff/papers.html#1976-01 . (shrink)

Computer and information ethics, as well as other fields of applied ethics, need ethical theories which coherently unify deontological and consequentialist aspects of ethical analysis. The proposed theory of just consequentialism emphasizes consequences of policies within the constraints of justice. This makes just consequentialism a practical and theoretically sound approach to ethical problems of computer and information ethics.

Whenever a structure with a particularly interesting computability-theoretic property is found, it is natural to ask whether similar examples can be found within well-known classes of algebraic structures, such as groups, rings, lattices, and so forth. One way to give positive answers to this question is to adapt the original proof to the new setting. However, this can be an unnecessary duplication of effort, and lacks generality. Another method is to code the original structure into a structure in the given (...) class in a way that is effective enough to preserve the property in which we are interested. In this paper, we show how to transfer a number of computability-theoretic properties from directed graphs to structures in the following classes: symmetric, irreflexive graphs; partial orderings; lattices; rings ; integral domains of arbitrary characteristic; commutative semigroups; and 2-step nilpotent groups. This allows us to show that several theorems about degree spectra of relations on computable structures, nonpreservation of computable categoricity, and degree spectra of structures remain true when we restrict our attention to structures in any of the classes on this list. The codings we present are general enough to be viewed as establishing that the theories mentioned above are computably complete in the sense that, for a wide range of computability-theoretic nonstructure type properties, if there are any examples of structures with such properties then there are such examples that are models of each of these theories. (shrink)

In the philosophy of chemistry a view is developed according to which laws of nature and scientific theories are peculiar in chemistry. This view was criticized in an earlier issue of the Foundations of Chemistry (Vihalemm, Foundation of Chemistry 5(1): 7–22, 2003) referring to an essay by Maureen and John Christie (Christie and Christie, in N. Bushan and S. Rosenfeld (Eds.), Of Minds and Molecules: New Philosophical Perspectives on Chemistry. Oxford University Press, New York, 2000, (...) pp. 34–50). This criticism was responded by the Christies (Christie and Christie, Foundations of Chemistry 5(2): 165–177, 2003). In the present article the debate is continued. The main issues which need to be elucidated in order to carry the analysis forward are pointed out and discussed. The relevance of a theoretical model of science for the philosophy of chemistry is stressed. (shrink)

Interest in the computational aspects of modeling has been steadily growing in philosophy of science. This paper aims to advance the discussion by articulating the way in which modeling and computational errors are related and by explaining the significance of error management strategies for the rational reconstruction of scientific practice. To this end, we first characterize the role and nature of modeling error in relation to a recipe for model construction known as Euler’s recipe. We then describe a (...) general model that allows us to assess the quality of numerical solutions in terms of measures of computational errors that are completely interpretable in terms of modeling error. Finally, we emphasize that this type of error analysis involves forms of perturbation analysis that go beyond the basic model-theoretical and statistical/probabilistic tools typically used to characterize the scientific method; this demands that we revise and complement our reconstructive toolbox in a way that can affect our normative image of science. (shrink)

Theoretical and Applied Issues Edited by Andrew Ortony Jon Slack Oliviero Stock NATO ASI Series Series F: Computer and Systems Sciences, Vol. 100 Communication from an Artificial Intelligence Perspective NATO ASI Series Advanced ...