Comprehensive when it was published in 1990, this guide brought together information on the broad spectrum of education and research opportunities then available in the sciences of complexity. Its purpose was to make these kinds of investigations more accessible by providing information on programs, institutions, organizations, and literature where one can learn about their principles, methods, and applications. The guide was intended to help interested students and educators locate the various academic fields, departments, institutes, and programs that offer education in (...) systems thinking and complex systems research. The guide also served professionals who are already involved in the systems sciences as a directory to general activity in what are otherwise widely separate fields. By browsing the guide one can get a snapshot of where education and research in systems science was happening at the time in both North America and Europe. The landscape has since massively changed so its value is mostly historical. (shrink)

The paper describes the design of an intelligent tutoring system for teaching Introduction to Computer Science-a compulsory curriculum in Al-Azhar University of Gaza to students who attend the university. The basic idea of this system is a systematic introduction into computer science. The system presents topics with examples. The system is dynamically checks student's individual progress. An initial evaluation study was done to investigate the effect of using the intelligent tutoring system on the performance of students enrolled in (...) computer science curriculum at Al-Azhar University, Gaza. The results showed a positive impact on the evaluators. (shrink)

This paper discusses the epistemic status of biology from the standpoint of the systemic approach to living systems based on the notion of biological autonomy. This approach aims to provide an understanding of the distinctive character of biological systems and this paper analyses its theoretical and epistemological dimensions. The paper argues that, considered from this perspective, biological systems are examples of emergent phenomena, that the biological domain exhibits special features with respect to other domains, and that biology (...) as a discipline employs some core concepts, such as teleology, function, regulation among others, that are irreducible to those employed in physics and chemistry. It addresses the claim made by Jacques Monod that biology as a science is marginal. It argues that biology is general insofar as it constitutes a paradigmatic example of complexity science, both in terms of how it defines the theoretical object of study and of the epistemology and heuristics employed. As such, biology may provide lessons that can be applied more widely to develop an epistemology of complex systems. (shrink)

It has been argued that ethical frameworks for data science often fail to foster ethical behavior, and they can be difficult to implement due to their vague and ambiguous nature. In order to overcome these limitations of current ethical frameworks, we propose to integrate the analysis of the connections between technical choices and sociocultural factors into the data science process, and show how these connections have consequences for what data subjects can do, accomplish, and be. Using healthcare as (...) an example, attention to sociocultural conversion factors relevant to health can help in navigating technical choices that require broader considerations of the sociotechnical system, such as metric tradeoffs in model validation, resulting in better ethical and technical choices. This approach promotes awareness of the ethical dimension of technical choices by data scientists and others, and that can foster the cultivation of 'ethical skills' as integral to data science. (shrink)

A cognitive science perspective of yoga system of thought will be developed in conjugation with the Samkhya Darsana. This development will be further advanced using Advaita Vedanta and will be translated into modern scientific terms to arrive at an idea about cognition process. The stalling of the cognitive process and stilling the mind will be critically discussed in the light of this perspective. This critical analysis and translation into cognitive science and modern scientific terms will be presented together (...) with its implications and applications to the disciplines of mind-machine modeling, natural language comprehension branch of artificial intelligence and physiological psychology. (shrink)

The reward system of science is the priority rule. The first scientist making a new discovery is rewarded with prestige, while second runners get little or nothing. Michael Strevens, following Philip Kitcher, defends this reward system, arguing that it incentivizes an efficient division of cognitive labor. I argue that this assessment depends on strong implicit assumptions about the replicability of findings. I question these assumptions on the basis of metascientific evidence and argue that the priority rule systematically discourages replication. (...) My analysis leads us to qualify Kitcher and Strevens’s contention that a priority-based reward system is normatively desirable for science. (shrink)

ITS (Intelligent Tutoring System) is a computer software that supplies direct and adaptive training or response to students without, or with little human teacher interfering. The main target of ITS is smoothing the learning-teaching process using the ultimate technology in computer science. The proposed system will be implemented using the “ITSB” Authoring tool. The book "Introduction To Computer Science" is taught in Al-Azhar University in Gaza as a compulsory subject for students who study at humanities faculties. In this (...) thesis, the researcher demonstrates an intelligent tutoring system for teaching the above mentioned subject. The system was assessed by a group of teachers and students and the results were promising . (shrink)

From his earliest work forward, phenomenologist Maurice Merleau-Ponty attempted to develop a new ontology of nature that would avoid the antinomies of realism and idealism by showing that nature has its own intrinsic sense which is prior to reflection. The key to this new ontology was the concept of form, which he appropriated from Gestalt psychology. However, Merleau-Ponty struggled to give a positive characterization of the phenomenon of form which would clarify its ontological status. Evan Thompson has recently taken up (...) Merleau-Ponty’s ontology as the basis for a new, “enactive” approach to cognitive science, synthesizing it with concepts from dynamic systems theory and Francisco Varela’s theory of autopoiesis. However, Thompson does not quite succeed in resolving the ambiguities in Merleau-Ponty’s account of form. This article builds on an indication from Thompson in order to propose a new account of form as asymmetry, and of the genesis of form in nature as symmetry-breaking. These concepts help us to escape the antinomies of Modern thought by showing how nature is the autoproduction of a sense which can only be known by an embodied perceiver. (shrink)

This paper presents the unification of all knowledge and the framework of all sciences, so it goes the theory of consciousness, the method to measure consciousness, and the three keys of the Strong AI. “Logicality and non-absoluteness” is found out to be the intrinsicality of nature, so the “Fundamental Law of Nature” is discovered. Then, the “general methodology of research” and the “model system of nature” are developed to explain everything, especially consciousness. The Coupling Theory of Consciousness tells that nature (...) has the MFEs (More Fundamental Element) that couple to show as material and consciousness, and the brain has a CNS (central nervous system)-independent consciousness system that couples to give off the consciousness signals, with their three excitation levels to show as memory, sub-consciousness, and subjective consciousness. As consciousness is not from neurons, the method to measure consciousness via NCC (neural correlates of consciousness) is to find out participants with the same kinds of consciousness systems. And make them to produce paralleled “conscious information processes” to filtrate out the “noise” neural activities, to obtain the “real” NCC data. Examining the property of consciousness may advance not only neuroscience and physics, but also cognitive science and AI technology. First, the “conscious information processing” model has shown that the Strong AI should process the beyond-domain concepts with a self-controlled intention, second, as the “general methodology of research” is just the other name of the “principle of cognition”, we have already known the running style of the Strong AI. Hopefully, we could develop the Strong AI technology to upgrade human civilization very soon. (shrink)

(See also the separate entry for the volume itself.) This introduction has three parts. The first providing an overview of some main lines of research in deontic logic: the emergence of SDL, Chisholm's paradox and the development of dyadic deontic logics, various other puzzles/challenges and areas of development, along with philosophical applications. The second part focus on some actual and potential fruitful interactions between deontic logic, computer science and artificial intelligence. These include applications of deontic logic to AI knowledge (...) representation in legal systems, to modelling computer systems where it is expected that sub-ideal states will emerge and require countermeasures, to norm-governed human interactions with computer systems, and to the representation of some features of multi-agent systems where different agent-like computer systems interact with one another. The third and final part briefly groups and previews the papers in the anthology. (shrink)

Vietnam, with a geographical proximity and a high volume of trade with China, was the first country to record an outbreak of the new Coronavirus disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 or SARS-CoV-2. While the country was expected to have a high risk of transmission, as of April 4, 2020—in comparison to attempts to contain the disease around the world—responses from Vietnam are being seen as prompt and effective in protecting the interests of its citizens, (...) with 239 confirmed cases and no fatalities. This study analyzes the situation in terms of Vietnam’s policy response, social media and science journalism. A self-made web crawl engine was used to scan and collect official media news related to COVID-19 between the beginning of January and April 4, yielding a comprehensive dataset of 14,952 news items. The findings shed light on how Vietnam—despite being under-resourced—has demonstrated political readiness to combat the emerging pandemic since the earliest days. Timely communication on any developments of the outbreak from the government and the media, combined with up-to-date research on the new virus by the Vietnamese science community, have altogether provided reliable sources of information. By emphasizing the need for immediate and genuine cooperation between government, civil society and private individuals, the case study offers valuable lessons for other nations concerning not only the concurrent fight against the COVID-19 pandemic but also the overall responses to a public health crisis. (shrink)

The comprehensive nature of information and insight available in the Upanishads, the Indian philosophical systems like the Advaita Philosophy, Sabdabrahma Siddhanta, Sphota Vaada and the Shaddarsanas, in relation to the idea of human consciousness, mind and its functions, cognitive science and scheme of human cognition and communication are presented. All this is highlighted with vivid classification of conscious-, cognitive-, functional- states of mind; by differentiating cognition as a combination of cognitive agent, cognizing element, cognized element; formation; form and (...) structure of cognition, instruments and means of cognition, validity of cognition and the nature of energy/matter which facilitates and also is the medium of cognition- cognizing process; and also as the container and content of cognition. The human communication process which is just the reverse of cognizing process is also presented with necessary description and detail. The sameness of cognitive / communicative process during language acquisition and communication processes and the modes of language acquisition and communication are also given. The hardware and software of human cognition, language acquisition and communication as envisaged in Indian spiritual and philosophical expressions are given. In the light of the information and insight obtained as above, the axioms for human cognition / communication are formed, framed and presented. A brain-wave frequency modulation / demodulation model of human cognition, communication and language acquisition and communication process based on Upanishadic expressions, Shaddarsanas and Sabdabrahma Siddhhanta is defined and discussed here. The use of these theories and models and axioms in mind-machine modelling and natural language comprehension branch of artificial intelligence will be put forward and highlighted. (shrink)

The nature and structure of time and time-intervals in physical, chemical and biological systems will be elucidated. The relation and dependence among time, energy and taking place of natural processes will be critically analyzed. The bio-processes taking place in nano-time intervals will be identified. Their relevance to nano-bio-science and nano-bio-technology will be developed and nano-time interval-aspect of nano-sciences and nano-technology will be advanced. -/- .

Academia is a competitive environment. Early Career Researchers (ECRs) are limited in experience and resources and especially need achievements to secure and expand their careers. To help with these issues, this book offers a new approach for conducting research using the combination of mindsponge innovative thinking and Bayesian analytics. This is not just another analytics book. 1. A new perspective on psychological processes: Mindsponge is a novel approach for examining the human mind’s information processing mechanism. This conceptual framework is used (...) to construct models in studies. The framework is highly flexible and widely applicable for many different types of information processes. The mindsponge approach can help researchers discover interesting ideas or even formulate their very own theories when investigating psychosocial phenomena. This approach brings a fresh wind to the current landscape of social sciences and humanities (SSH). 2. Easy-to-follow analysis protocol: The Bayesian Mindsponge Framework (BMF analytics) is useful in terms of computing and visualizing power but also easy to learn and apply. Contrary to being intimidating, the Bayesian analytics section of this book is presented in a reader-friendly manner with a detailed yet clear step-by-step procedure. Examples are from published BMF articles, allowing readers to immediately practice the method and quickly create their own applications. With educational purposes in mind, the book is very suitable for ECRs who are looking to innovate their research methods. 3. Advocating for low-cost, high-quality research: Doing science can be very costly. Mindsponge innovative thinking and BMF analytics help produce impactful studies using openly available data on online repositories. This is based on the authors’ previous works and experiences. The book presents examples of employing the open R package bayesvl on secondary data from different sources. With less financial constraints, researchers can have more freedom of thought to pursue their curiosity and creativity. ECRs in low- and middle-income countries may find this aspect crucial in their careers. 4. Support and collaboration: The authors share their insights from experiences in the academic publishing system to help readers get through the processes of manuscript writing and peer-reviewing more easily. The authors are also ready to support other researchers with further inquiries and collaboration opportunities at the following website, mindsponge(dot)info. This book is for: a) ECRs whose only abundant resources are their innovation capacity and strength of will; b) Researchers in SSH who want to explore a novel approach to thinking and study conducting; c) Low- and middle-income countries’ researchers looking for a cost-effective research protocol; and, d) Innovative thinkers who want to turn their interesting thoughts into good publications. (shrink)

WikiSilo is a tool for theorizing across interdisciplinary fields such as Cognitive Science, and provides a vocabulary for talking about the problems of doing so. It can be used to demonstrate that a particular cognitive theory is complete and coherent at multiple levels of discourse, and commensurable with and relevant to a wider domain of cognition. WikiSilo is also a minimalist theory and methodology for effectively doing science. WikiSilo is simultaneously similar to and distinct, as well as integrated (...) and separated from Wikipedia™. This paper will introduce the advantages of WikiSilo for use in the Cognitive Sciences. (shrink)

The evolution of Intelligent Tutoring System (ITS) is the result of the amount of research in the field of education and artificial intelligence in recent years. English is the third most common languages in the world and also is the internationally dominant in the telecommunications, science and trade, aviation, entertainment, radio and diplomatic language as most of the areas of work now taught in English. Therefore, the demand for learning English has increased. In this paper, we describe the design (...) of an Intelligent Tutoring System for teaching English language grammar to help students learn English grammar easily and smoothly. The system provides all topics of English grammar and generates a series of questions automatically for each topic for the students to solve. The system adapts with all the individual differences of students and begins gradually with students from easier to harder level. The intelligent tutoring system was given to a group of students of all age groups to try it and to see the impact of the system on students. The results showed a good satisfaction of the students toward the system. (shrink)

Indian spiritual and philosophical systems are essentially cognitive scientific in nature. Having origin in the Upanishads all Indian philosophical systems supplemented and complemented one another to develop a comprehensive source book of cognitive science. The nature and form of consciousness, mind and its functions are extensively dealt with and discussed from Upanishads through Buddhism, Jainism, Viseshaka, Nyaya, Yoga, Samkhya, Poorva Meemamsa,and Uttara Meemaams, Sabdabrahma Siddhanta contributing to many concepts which have relevance to cognitive science and language (...) acquisition and communication. In this paper all these will be reviewed and especially the concept of guṇa as envisaged in various Indian philosophical systems will be presented and correlated. The evolution of concept of guṇa through Shaddrarsanas will be specifically looked at. A correlation with Sabdabrahma Siddhānta of Indian grammarians initiated by Patanjali and developed through Bhartruhari will also be presented. (shrink)

In this chapter, we argue that in order to understand the interdisciplinary and transdisciplinary dialectics in sustainability science, it is useful to see sustainability science as a kind of management science, and then to highlight the hard-soft distinction in systems thinking. First, we argue that the commonly made natural-social science dichotomy is relatively unimportant and unhelpful. We then outline the differences between soft and hard systems thinking as a more relevant and helpful distinction, mainly (...) as a difference between perspectives in systemic modeling toward models. We also illustrate that the distinction is methodologically useful to advance sustainability science by enabling us (i) to suggest novel ways of using existing theoretical, experimental, and computational resources of the sciences for renewable resource management, and (ii) to disentangle disciplinary disagreements in climate science. (shrink)

The human body is a system made of systems. The body is divided into bodily systems proper, such as the endocrine and circulatory systems, which are subdivided into many sub-systems at a variety of levels, whereby all systems and subsystems engage in massive causal interaction with each other and with their surrounding environments. Here we offer an explicit definition of bodily system and provide a framework for understanding their causal interactions. Medical sciences provide at best (...) informal accounts of basic notions such as system, process, and function, and while such informality is acceptable in documentation created for human beings, it falls short of what is needed for computer representations. In our analysis we will accordingly provide the framework for a formal definition of bodily system and of associated notions. (shrink)

In this book I show that science suffers from a damaging but rarely noticed methodological disease, which I call rationalistic neurosis. It is not just the natural sciences which suffer from this condition. The contagion has spread to the social sciences, to philosophy, to the humanities more generally, and to education. The whole academic enterprise, indeed, suffers from versions of the disease. It has extraordinarily damaging long-term consequences. For it has the effect of preventing us from developing traditions and (...) institutions of learning rationally devoted to helping us learn how to make progress towards a wiser, more civilized world. On our fragile earth, overcrowded, fraught with injustice, inequality and conflict, menaced by unprecedented and terrifying technological and industrial means for change and destruction, we urgently need to acquire a little more wisdom and civilization if we are to avoid repeating horrors of the kind suffered by so many during the 20th century (and already suffered by many in the first few years of the 21st century). We can ill afford to have in our hands instruments of learning botched and bungled from the standpoint of helping us learn how to live more wisely. It may seem scarcely credible that something as important as our institutions of learning can suffer from wholesale, structural defects. Why has this not been noticed before? Why have not armies of scientists and scholars appreciated the point and, long ago, put the matter right? The answer will emerge as my argument unfolds. I will show that one of the most damaging features of rationalistic neurosis is that it has built-in methodological and institutional mechanisms which effectively conceal that anything is wrong. But there is also an immediately obvious reason: specialization, and the resulting fragmentation of academia, has resulted in a situation in which hardly anyone takes responsibility for the overall ideals, the overall aims and methods, of academic inquiry. Academics, these days, are specialists, furiously trying to keep abreast of developments in their own specialist fields. They have no time, and no inducement, to lift their eyes from their particular disciplines, and look at the whole endeavour. Science has long been under attack, at least since the Romantic movement. Blake objected to “Single vision & Newton’s sleep” and declared that “Art is the Tree of Life... Science is the Tree of Death”. Keats lamented that science will “clip an Angel’s wings” and “unweave a rainbow”. Whereas the Enlightenment had valued science and reason as tools for the liberation of humanity, Romanticism found science and reason oppressive and destructive, and instead valued art, imagination, inspiration, individual genius, emotional and motivational honesty rather than careful attention to objective fact. Much subsequent opposition to science stems from, or echoes, the Romantic opposition of Blake, Wordsworth, Keats and many others. There is the movement Isaiah Berlin has described as the “Counter-Enlightenment” (Berlin, 1979, ch. 1). There is existentialism, with its denunciation of the tyranny of reason, its passionate affirmation of the value and centrality of irrationality in human life, from Dostoevsky, Kierkegaard and Nietzsche to Heidegger and Sartre (see, for example, Barrett, 1962). There is the attack on Enlightenment ideals concerning science and reason undertaken by the Frankfurt school, by postmodernists and others, from Horkheimer and Adorno to Lyotard, Foucault, Habermas, Derrida, MacIntyre and Rorty (see Gascardi, 1999). The soul-destroying consequences of valuing science and reason too highly is a persistent theme in literature: it is to be found in the works of writers such as D.H. Lawrence, Doris Lessing, Max Frisch, Y. Zamyatin. There is persistent opposition to modern science and technology, and to scientific rationality, often associated with the Romantic wing of the green movement, and given expression in such popular books as Marcuse’s One Dimensional Man, Roszak’s Where the Wasteland Ends, Berman’s The Reenchantment of the World and Appleyard’s Understanding the Present. There is the feminist critique of science and conceptions of science: see, for example, Fox Keller (1984) and Harding (1986). And there are the corrosive implications of the so-called “strong programme” in the sociology of knowledge, and of the work of social constructivist historians of science, which depict scientific knowledge as a belief system alongside many other such conflicting systems, having no more right to claim to constitute knowledge of the truth than these rivals, the scientific view of the world being no more than an elaborate myth, a social construct (see Barnes and Bloor, 1981; Bloor, 1991; Barnes, Bloor and Henry, 1996; Shapin and Schaffer, 1985; Shapin, 1994; Pickering, 1984; Latour, 1987). This latter literature has provoked a counter-attack by scientists, historians and philosophers of science seeking to defend science and traditional conceptions of scientific rationality: see Gross and Levitt (1994), Gross, Levitt and Lewis (1996), and Koertge (1998). This debate between critics and defenders of science came abruptly to public attention with the publication of Alan Sokal’s brilliant hoax article ‘Transgressing the boundaries’ in a special issue of the cultural studies journal Social Text in 1996 entitled Science Wars: see Sokal and Bricmont (1998). What does this book have to contribute, given the above avalanche of criticism of science? The criticisms of science developed in this book are diametrically opposed to the above, in so far as the above criticisms oppose scientific rationality, seek to diminish or restrict its influence, or hold that it is unattainable. My central point is that we suffer, not from too much scientific rationality, but from not enough. What is generally taken to constitute scientific rationality is actually nothing of the kind. It is rationalistic neurosis, a characteristic, influential and damaging kind of irrationality masquerading as rationality. Science is damaged by being trapped within a widely upheld but severely defective philosophy of science; free science from this defective philosophy, provide it with a more intellectually rigorous philosophy, and it will flourish in both intellectual and humanitarian terms. And more generally, as we shall see, academic inquiry as a whole is damaged by being trapped within an intellectually defective philosophy of inquiry; free it from this defective philosophy, from its rationalistic neurosis, and it will flourish in intellectual and human terms. It is not reason that is damaging, but defective pretensions to reason — rationalistic neurosis —masquerading as reason. Thus what I seek to do here is the exact opposite of what all those who oppose science and scientific rationality do. I shall argue that Reason, the authentic article, arrived at by generalizing the progress-achieving methods of science, can have profoundly liberating and enriching consequences for all worthwhile, problematic aspects of life, and thus deserves to enter into every aspect of life. The bare bones of the argument of this book can be stated quite simply like this. Science cannot proceed without making the substantial metaphysical assumption that the universe is physically comprehensible (to some extent at least). But this conflicts with the orthodox view that in science everything is assessed impartially with respect to evidence, nothing being permanently assumed independently of evidence. So the metaphysical assumption of comprehensibility is repressed. Science pretends that no such assumption is made. But this damages science. For the assumption is substantial, influential and highly problematic. It needs to be made explicit within science so that it can be critically scrutinized, so that alternatives can be developed and considered. Pretending the assumption is not being made undermines the intellectual rigour of science, its intellectual value and success. And it does not stop there. For science also makes value assumptions. Quite properly, science is concerned to discover that which is of value. New factual knowledge devoid of all value (whether intellectual or practical) does not contribute to science. But the orthodox view of science holds that values have no place within science. As in the case of metaphysics, here too, science pretends that values have no role to play within the intellectual domain of science. And this damages science. For values are, if anything, even more influential and problematic than metaphysics (in influencing the direction of research). Here too, values need to be made explicit within science so that they can be scrutinized, so that alternatives can be developed and assessed. Pretending that values play no role within the intellectual domain damages science; both the intellectual and the practical aspects of science are adversely affected. Science fails to pursue those avenues of research that lie in the best interests of humanity. And it goes further. Science is pursued in a social, cultural, economic and political context. It is a part of various social, economic and political projects which seek to achieve diverse human objectives. But the idea that science is an integral part of humanitarian or political enterprises with political ends clashes, once again, with the official view of science that the aim of science is to improve factual knowledge. The political objectives of science are repressed. And, once again, this damages science. For, of course, the political objectives of science, like all our political objectives, are profoundly problematic. These need to be made explicit so that they can be scrutinized, so that alternatives can be developed and considered. The pretence that science does not have this political dimension once again undermines the intellectual rigour of science, and its human value. It lays science open to becoming a part of economic, corporate and political enterprises that are not in the best interests of humanity. The upshot of the line of argument just indicated is that we need to bring about a revolution in the aims and methods of science, and of academic inquiry more generally. Natural science needs to change; its relationship with the rest of academic inquiry, with social inquiry and the humanities, needs to change; and most importantly and dramatically, academic inquiry as a whole needs to change. The basic task of the academic enterprise needs to become to help humanity learn how to tackle its problems of living in more cooperatively rational ways than at present. We need to put the intellectual tasks of articulating our problems of living, and proposing and critically assessing possible solutions, possible and actual actions, at the heart of academic inquiry. The basic task needs to be to help humanity learn a bit more wisdom – wisdom being the capacity to realize what is of value in life, for oneself and others, wisdom including knowledge and technological know-how, but much else besides. Natural science, despite its flaws, has massively increased our knowledge and technological know-how. This in turn has led to a massive and sometimes terrifying increase in our power to act. Often this unprecedented power to act is used for human good, as in medicine or agriculture. But it is also used to cause harm, whether unintentionally (initially at least) as when industrialization and modern agriculture lead to global warming, destruction of natural habitats and rapid extinction of species, or intentionally, as when the technology of war is used by governments and terrorists to maim and kill. Before the advent of modern science, when we lacked the means to do too much damage to ourselves and the planet, lack of wisdom did not matter too much. Now, with our unprecedented powers to act, bequeathed to us by science, lack of wisdom has become a menace. This is the crisis behind all the other current global crises: science without wisdom. In these circumstances, to continue to pursue knowledge and technological know-how dissociated from a more fundamental quest for wisdom can only deepen the crisis. As a matter of urgency, we need to free science and academia of their neuroses; we need to bring about a revolution in the academic enterprise so that the basic aim becomes to promote wisdom by intellectual and educational means. At present science and the humanities betray both reason and humanity. The argument of this book, which I have just summarized, begins with a discussion of the philosophical and methodological problems that beset theoretical physics. At once, many of those who are concerned about moral, political and environmental issues that plague our world today, will feel impatient. What have the methodological problems of theoretical physics to do with third world poverty, war and the threat of war, pollution, extinction of species, the menace of conventional, chemical, biological and nuclear armaments? I can only plead with such a reader: patience. The root cause of the sickness of our times does indeed lie, I claim, with a methodological sickness of natural science or, even more specifically, of physical science. What makes the modern world so utterly different from all previous ages is our possession of modern science and technology. This is the instrument that has changed the conditions of human life almost beyond all recognition, and put unprecedented, and sometimes terrifying, powers into our hands. One should not dismiss out of hand the suggestion that a part of our problem may lie with this instrument, this engine, of rapid change. We see, here, too, the way in which intellectual specialization, referred to above, has effectively concealed from view the nature and extent of the problem that confronts us. The argument that I shall develop in what follows begins with physics, with problems concerning the aims and methods of physics. But it then leaps to social science, to philosophy, to the humanities, to education, to psychotherapy, and to politics: in the end there is scarcely an aspect of modern life that is not touched and, potentially, affected by the argument. How many academic experts are prepared to follow, to take seriously, an argument that ranges so recklessly across such a wide range of academic disciplines? How many non-academic non-experts? But just this is what the argument and message of this book requires. I hope that the reader will endure with patience the somewhat esoteric discussion concerning the aims and methods of physics pursued in chapter one. This may not seem to have anything much to do with the urgent problems of our times, but it does. This is in part how the intellectual disaster I seek to expose in this book conceals itself from view: it buries itself in the obscure, recondite field of the philosophy of physics. Those who devote their lives to the philosophy of physics are, by and large, too myopic to see how their specialized field of study has anything to do with the great and dreadful humanitarian problems and disasters of our age; and those who are above all concerned with these humanitarian disasters have no time at all for abstruse issues concerning the aims and methods of physics. And so the connection is never made. As it happens, the methodological neurosis of physics, with which we begin in chapter one, is actually a quite simple matter to grasp. It does not require any real knowledge of physics to understand. Indeed, physicists and philosophers of physics are much more likely to find the argument difficult to follow than are non-experts. We non-scientists can stand back and see the whole wood; scientists, trained to think in terms of the current orthodox conception of science, trapped in the thickets of research, will find this much harder to do. In an attempt to take this peculiar circumstance into account, I have arranged the exposition as follows. In chapter one I give a simple exposition of the case for declaring natural science to suffer from what I call "rationalistic neurosis"; this avoids all technicalities, and goes straight to the heart of the matter. In the appendix I tackle a host of more technical objections that may be made to the elementary argument of chapter one. So, those experts in the fields of the philosophy of physics and philosophy of science who find the argument of chapter one naïve and unconvincing, should consult the appendix before tossing the book away in disgust. I write in the hope that there will be a few who will not dismiss out of hand the suggestion that the question of how we are to go about learning how to live in wiser and more civilized ways might have something to learn from scientific learning, and will take the trouble to pursue the line of argument traced out in this book. I write in the hope that these few will grasp just how desperate our situation is, how urgent the need to change the status quo, and will do everything in their power to alert others to the need to heal the methodological sickness from which our institutions and traditions of learning at present suffer. To begin with, we need a campaigning organization, modelled perhaps on "Friends of the Earth", which might be called something like "Friends of Wisdom". (shrink)

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the (...) limits of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum. (shrink)

Consciousness has been the bone of contention for philosophers throughout centuries. Indian philosophy largely adopted lived experience as the starting point for its explorations of consciousness. For this reason, from the very beginning, experience was an integral way of grasping consciousness, whose validity as a tool was considered self-evident. Thus, in Indian philosophy, the question was not to move from the brain to mind but to understand experience of an individual and how such an experience is determined through mental structures (...) (and secondarily, the preoccupation with the brain and its relation to the mind). In contrast, cognitive science (the study of mind and cognition through 1 interdisciplinary methods, with emphasis on computational methods) found its debates soaked in discussion which primarily involved the brain and mind. Experience was not considered a primary source of information and its validity had to be established to consider it a source of information of mind. With the rise of physicalism and realization that mental states are correlative to brain states, the body was virtually neglected from involvement in understanding the mind and the attempts to reduce mind to the brain were rampant. The inability to explain subjective experience of an individual through neuroscientific findings alone has urged philosophers to explore other ways of understanding the ontology of mind. Over the last few years, embodied cognition and enactive approach have brought back the body as a central participant in this debate, providing fertile grounds to explain the relation of brain, body and mind. This paper proposes that we understand the brain as a complex system from which the mind emerges. This emergence is marked by the development of novel property of self-consciousness in human beings. The mind is a process which is embedded throughout the body and thus, the body acts as an actualizing medium for the individual. Thus, the brain is a necessary condition for the mind to be while the mind is embedded throughout the body. The brain and mind are in reciprocal causal relationship with one another, as is the body and environment with one another. In this paper, embodied cognition is understood through principles of Merleau Ponty's idea of embodiment, than through Andy Clark and Francis Varela's alone. (shrink)

This essay presents the conditional probability of co-contribution account of the individuation of cognitive systems (CPC) and argues that CPC provides an attractive basis for a theory of the cognitive self. The argument proceeds in a largely indirect way, by emphasizing empirical challenges faced by an approach that relies entirely on predictive processing (PP) mechanisms to ground a theory of the cognitive self. Given the challenges faced by PP-based approaches, we should prefer a theory of the cognitive self of (...) the sort CPC offers, one that accommodates variety in the kinds of mechanism that, when integrated, constitute a cognitive system (and thus the cognitive self), to a theory according to which the cognitive self is composed of essentially one kind of thing, for instance, prediction-error minimization mechanisms. The final section focuses on one of the central functions of the cognitive self: to engage in conscious reasoning. It is argued that the phenomenon of conscious, deliberate reasoning poses an apparently insoluble problem for a PP-based view, one that seems to rest on a structural limitation of predictive-processing models. In a nutshell, conscious reasoning is a single-stream phenomenon, but, in order for PP to apply, two streams of activity must be involved, a prediction stream and an input stream. Thus, with regard to the question of the nature of the self, PP-based views must yield to an alternative approach, regardless of whether proponents of the predictive processing, as a comprehensive theory of cognition, can handle the various empirical challenges canvassed in the preceding section. (shrink)

The empirical study of belief is emerging at a rapid clip, uniting work from all corners of cognitive science. Reliance on belief in understanding and predicting behavior is widespread. Examples can be found, inter alia, in the placebo, attribution theory, theory of mind, and comparative psychological literatures. Research on belief also provides evidence for robust generalizations, including about how we fix, store, and change our beliefs. Evidence supports the existence of a Spinozan system of belief fixation: one that is (...) automatic and independent of belief rejection. Independent research supports the existence of a system of fragmented belief storage: one that relies on large numbers of causally isolated, context-sensitive stores of belief in memory. Finally, empirical and observational data support at least two systems of belief change. One system adheres, mostly, to epistemological norms of updating; the other, the psychological immune system, functions to guard our most centrally held beliefs from potential inconsistency with newly formed beliefs. Refining our under- standing of these systems can shed light on pressing real-world issues, such as how fake news, propaganda, and brainwashing exploit our psychology of belief, and how best to construct our modern informational world. (shrink)

Medical science conceives the human body as a system comprised of many subsystems at a variety of levels. At the highest level are bodily systems proper, such as the endocrine system, which are central to our understanding of human anatomy, and play a key role in diagnosis and in dynamic modeling as well as in medical pedagogy and computer visualization. But there is no explicit definition of what a bodily system is; such informality is acceptable in documentation created (...) for human beings, but falls short of what is needed for computer representations. Our analysis is intended as a first step towards filling this gap. (shrink)

Humean reductionism about laws of nature appears to leave a central aspect of scientific practice unmotivated: If the world’s fundamental structure is exhausted by the actual distribution of non-modal properties and the laws of nature are merely efficient summaries of this distribution, then why does science posit laws that cover a wide range of non-actual circumstances? In this paper, we develop a new version of the Humean best systems account of laws based on the idea that laws need (...) to organize information in a way that maximizes their cognitive usefulness for creature like us. We argue that this account motivates scientific practice because the laws’ applicability to non-actual circumstances falls right out of their cognitive usefulness. (shrink)

The term “Complex Systems Biology” was introduced a few years ago [Kaneko, 2006] and, although not yet of widespread use, it seems particularly well suited to indicate an approach to biology which is well rooted in complex systems science. Although broad generalizations are always dangerous, it is safe to state that mainstream biology has been largely dominated by a gene-centric view in the last decades, due to the success of molecular biology. So the one gene - one (...) trait approch, which has often proved to be effective, has been extended to cover even complex traits. This simplifying view has been appropriately criticized, and the movement called systems biology has taken off. Systems biology [Noble, 2006] emphasizes the presence of several feedback loops in biological systems, which severely limit the range of validity of explanations based upon linear causal chains (e.g. gene → behaviour). Mathematical modelling is one the favourite tools of systems biologists to analyze the possible effects of competing negative and positive feedback loops which can be observed at several levels (from molecules to organelles, cells, tissues, organs, organisms, ecosystems). Systems biology is by now a well-established field, as it can be inferred by the rapid growth in number of conferences and journals devoted to it, as well as by the existence of several grants and funded projects.Systems biology is mainly focused upon the description of specific biological items, like for example specific organisms, or specific organs in a class of animals, or specific genetic-metabolic circuits. It therefore leaves open the issue of the search for general principles of biological organization, which apply to all living beings or to at least to broad classes. We know indeed that there are some principles of this kind, biological evolution being the most famous one. The theory of cellular organization also qualifies as a general principle. But the main focus of biological research has been that of studying specific cases, with some reluctance to accept (and perhaps a limited interest for) broad generalizations. This may however change, and this is indeed the challenge of complex systems biology: looking for general principles in biological systems, in the spirit of complex systems science which searches for similar features and behaviours in various kinds of systems. The hope to find such general principles appears well founded, and I will show in Section 2 that there are indeed data which provide support to this claim. Besides data, there are also general ideas and models concerning the way in which biological systems work. The strategy, in this case, is that of introducing simplified models of biological organisms or processes, and to look for their generic properties: this term, borrowed from statistical physics, is used for those properties which are shared by a wide class of systems. In order to model these properties, the most effective approach has been so far that of using ensembles of systems, where each member can be different from another one, and to look for those properties which are widespread. This approach was introduced many years ago [Kauffman, 1971] in modelling gene regulatory networks. At that time one had very few information about the way in which the expression of a given gene affects that of other genes, apart from the fact that this influence is real and can be studied in few selected cases (like e.g. the lactose metabolism in E. coli). Today, after many years of triumphs of molecular biology, much more has been discovered, however the possibility of describing a complete map of gene-gene interactions in a moderately complex organism is still out of reach. Therefore the goal of fully describing a network of interacting genes in a real organism could not be (and still cannot be) achieved. But a different approach has proven very fruitful, that of asking what are the typical properties of such a set of interacting genes. Making some plausible hypotheses and introducing some simplifying assumptions, Kauffman was able to address some important problems. In particular, he drew attention to the fact that a dynamical system of interacting genes displays selforganizing properties which explain some key aspects of life, most notably the existence of a limited number of cellular types in every multicellular organism (these numbers are of the order of a few hundreds, while the number of theoretically possible types, absent interactions, would be much much larger than the number of protons in the universe). In section 3 I will describe the ensemble based approach in the context of gene regulatory networks, and I will show that it can describe some important experimental data. Finally, in section 4 I will discuss some methodological aspects. (shrink)

In this article, network science is discussed from a methodological perspective, and two central theses are defended. The first is that network science exploits the very properties that make a system complex. Rather than using idealization techniques to strip those properties away, as is standard practice in other areas of science, network science brings them to the fore, and uses them to furnish new forms of explanation. The second thesis is that network representations are particularly helpful (...) in explaining the properties of non-decomposable systems. Where part-whole decomposition is not possible, network science provides a much-needed alternative method of compressing information about the behavior of complex systems, and does so without succumbing to problems associated with combinatorial explosion. The article concludes with a comparison between the uses of network representation analyzed in the main discussion, and an entirely distinct use of network representation that has recently been discussed in connection with mechanistic modeling. (shrink)

There is a deeply entrenched view in philosophy and physics, the closed systems view, according to which isolated systems are conceived of as fundamental. On this view, when a system is under the influence of its environment this is described in terms of a coupling between it and a separate system which taken together are isolated. We argue against this view, and in favor of the alternative open systems view, for which systems interacting with their environment (...) are conceived of as fundamental, and the environment's influence is represented via the dynamical equations that govern the system's evolution. Taking quantum theories of closed and open systems as our case study, and considering three alternative notions of fundamentality: (i) ontic fundamentality, (ii) epistemic fundamentality, and (iii) explanatory fundamentality, we argue that the open systems view is fundamental, and that this has important implications for the philosophy of physics, the philosophy of science, and for metaphysics. (shrink)

This paper explains and defends the idea that metaphysical necessity is the strongest kind of objective necessity. Plausible closure conditions on the family of objective modalities are shown to entail that the logic of metaphysical necessity is S5. Evidence is provided that some objective modalities are studied in the natural sciences. In particular, the modal assumptions implicit in physical applications of dynamical systems theory are made explicit by using such systems to define models of a modal temporal logic. (...) Those assumptions arguably include some necessitist principles. -/- Too often, philosophers have discussed ‘metaphysical’ modality — possibility, contingency, necessity — in isolation. Yet metaphysical modality is just a special case of a broad range of modalities, which we may call ‘objective’ by contrast with epistemic and doxastic modalities, and indeed deontic and teleological ones (compare the distinction between objective probabilities and epistemic or subjective probabilities). Thus metaphysical possibility, physical possibility and immediate practical possibility are all types of objective possibility. We should study the metaphysics and epistemology of metaphysical modality as part of a broader study of the metaphysics and epistemology of the objective modalities, on pain of radical misunderstanding. Since objective modalities are in general open to, and receive, natural scientific investigation, we should not treat the metaphysics and epistemology of metaphysical modality in isolation from the metaphysics and epistemology of the natural sciences. -/- In what follows, Section 1 gives a preliminary sketch of metaphysical modality and its place in the general category of objective modality. Section 2 reviews some familiar forms of scepticism about metaphysical modality in that light. Later sections explore a few of the many ways in which natural science deals with questions of objective modality, including questions of quantified modal logic. (shrink)

Purpose A mixed-method study was performed to determine the impact of integrating systems thinking (ST) into an electronic learning module for junior high school teachers in the Philippines. The study aims to assess how an ST approach to pedagogy compared against a conventional approach in terms of contribution to the participants’ global climate change content knowledge, holistic thinking and depth and accuracy of knowledge and reasoning. -/- Design/methodology/approach The study implemented e-learning modules using an ST approach versus a conventional (...) approach in teaching climate science to junior high school teachers. The paper presents quantitative data obtained from pre and posttests results of the 20 teacher-participants and qualitative data obtained during the focus-group discussion (FGD) after the implementation of the study. -/- Findings The results from the statistical analysis indicated that the ST group obtained a significant increase in their assessment scores compared to the non-ST group, according to predetermined criteria. Content knowledge, depth and accuracy of knowledge and reasoning increased the most. The participants mentioned during the FGD that the module helped deepen their understanding of climate change. -/- Research limitations/implications The study was limited to 20 teacher-participants, but it has relevance for public school teachers in the country given that participants had raised concerns regarding the lack of training in their schools for teaching climate science. They admitted that they lacked critical information to include in climate change topics in their classes. -/- Originality/value This paper shows how the ST approach can be used to teach climate change to junior high students. The e-learning module can provide teachers with better understanding, knowledge and reasoning to teach climate change to high school students more effectively. (shrink)

Open science will make science more efficient, reliable, and responsive to societal challenges. The European Commission has sought to advance open science policy from its inception in a holistic and integrated way, covering all aspects of the research cycle from scientific discovery and review to sharing knowledge, publishing, and outreach. We present the steps taken with a forward-looking perspective on the challenges laying ahead, in particular the necessary change of the rewards and incentives system for researchers (for (...) which various actors are co-responsible and which goes beyond the mandate of the European Commission). Finally, we discuss the role of artificial intelligence (AI) within an open science perspective. (shrink)

This paper combines two ideas: (1) That the Lewisian best system analysis of lawhood (BSA) can cope with laws that have exceptions (cf. Braddon-Mitchell in Noûs 35(2):260–277, 2001; Schrenk in The metaphysics of ceteris paribus laws. Ontos, Frankfurt, 2007). (2) That a BSA can be executed not only on the mosaic of perfectly natural properties but also on any set of special science properties (cf., inter alia, Schrenk 2007, Selected papers contributed to the sections of GAP.6, 6th international congress (...) of the society for analytical philosophy. Mentis, Paderborn/Münster, 2008; Cohen and Callender in Philos Stud 145:1–34, 2009, Erkenntnis 73:427–447, 2010). Bringing together (1) and (2) results in an analysis of special science ceteris paribus laws. (shrink)

I examine explanations’ realist commitments in relation to dynamical systems theory. First I rebut an ‘explanatory indispensability argument’ for mathematical realism from the explanatory power of phase spaces (Lyon and Colyvan 2007). Then I critically consider a possible way of strengthening the indispensability argument by reference to attractors in dynamical systems theory. The take-home message is that understanding of the modal character of explanations (in dynamical systems theory) can undermine platonist arguments from explanatory indispensability.

Recently, due to the rapid progress of computer technology, researchers develop an effective computer program to enhance the achievement of the student in learning process, which is Intelligent Tutoring System (ITS). Science is important because it influences most aspects of everyday life, including food, energy, medicine, leisure activities and more. So learning science subject at school is very useful, but the students face some problem in learning it. So we designed an ITS system to help them understand this (...) subject easily and smoothly by analyzing it and explaining it in a systematic way. In this paper, we describe the design of an Intelligent Tutoring System for teaching science for grade seven to help students know the 7 characteristics for living things smoothly. The system provides all topics of living things and generates some questions for each topic and the students should answer these questions correctly to move to the next level. In the result of an evaluation of the ITS, students like the system and they said that it is very useful for them and for their studies. (shrink)

In a development that has still been hardly noticed by philosophers, a conception of ontology has been advanced in recent years in a series of extra-philosophical disciplines as researchers in linguistics, psychology, geography and anthropology have sought to elicit the ontological commitments (‘ontologies’, in the plural) of different cultures or disciplines. Exploiting the terminology of Quine, researchers in psychology and anthropology have sought to establish what individual human subjects, or entire human cultures, are committed to, ontologically, in their everyday cognition, (...) in much the same way in which philosophers of science have attempted to elicit the ontological commitments of the natural sciences. Thus they have engaged in inquiries designed to establish how folk ontologies (or folk biologies, folk theories of physics, folk psychologies, and so on) develop through infancy and childhood, or to establish the degree to which given elements of folk ontologies reflect universal features of the human cognitive system. In a parallel development, researchers in biomedicine developed what they called 'ontologies' as controlled vocabularies to ensure interoperability of the way in which, for example, genomic data is described in different biological disciplines. We describe in what follows some of the relations between these efforts and the more traditional concerns of philosophers. (shrink)

The professor of psychopathology Simon Baron-Cohen claims that males are on average stronger at systematizing than empathizing and females are on average stronger at empathizing than systematizing. Systematizing is defined as the drive to construct or understand systems. In this paper, I observe that Baron-Cohen overlooks certain examples of systems, examples which lead to doubts about his claim.

The concept of similar systems arose in physics, and appears to have originated with Newton in the seventeenth century. This chapter provides a critical history of the concept of physically similar systems, the twentieth century concept into which it developed. The concept was used in the nineteenth century in various fields of engineering, theoretical physics and theoretical and experimental hydrodynamics. In 1914, it was articulated in terms of ideas developed in the eighteenth century and used in nineteenth century (...) mathematics and mechanics: equations, functions and dimensional analysis. The terminology physically similar systems was proposed for this new characterization of similar systems by the physicist Edgar Buckingham. Related work by Vaschy, Bertrand, and Riabouchinsky had appeared by then. The concept is very powerful in studying physical phenomena both theoretically and experimentally. As it is not currently part of the core curricula of STEM disciplines or philosophy of science, it is not as well known as it ought to be. (shrink)

It has been argued that our currently most satisfactory social epistemology of science can’t account for science that is based on artificial intelligence (AI) because this social epistemology requires trust between scientists that can take full responsibility for the research tools they use, and scientists can’t take full responsibility for the AI tools they use since these systems are epistemically opaque. I think this argument overlooks that much AI-based science can be done without opaque models, and (...) that agents can take full responsibility for the systems they use even if these systems are opaque. Requiring that an agent fully understand how a system works is an untenably strong condition for that agent to take full responsibility for the system and risks absolving AI developers from responsibility for their products. AI-based science need not create trust-related social epistemological problems if we keep in mind that what makes both individual scientists and their use of AI systems trustworthy isn’t full transparency of the internal processing but their adherence to social and institutional norms that ensure that scientific claims can be trusted. (shrink)

Pierre-Sylvain Régis’s Cartesianism is quite singular in seventeenth-century French philosophy. Though, can we speak of a form of experimental science in Régis’s work? After exploring his notions of ‘system’ and ‘hypothesis’, I will define his position in relation to Claude Perrault, Jacques Rohault, and the Royal Society. I argue, first, that the contrasts which traverse French science are not so much about the use of experiments but about whether or not observational data can be traced back to hypotheses (...) and to a coherent system. Secondly, that we can detect a significant similarity between Boyle’s positions and the views expressed by Perrault and also by Régis. Lastly, that French science, even in its Cartesian version, is much more probabilistic than English experimental philosophy. (shrink)

This paper considers the question of whether the influential distinction between levels of explanation introduced by David Marr can be used as a general framework for contemplating levels of explanation in cognitive sciences. Marr introduced three levels at which we can explain cognitive processes: the computational, algorithmic, and implementational levels. Some argue that Marr’s levels of explanation can only be applied to modular cognitive systems. However, since many psychological processes are non-modular, it seems that Marr’s levels of explanation cannot (...) explain such psychological processes. To show that the latter claim is not convincing, the paper draws upon an influential paradigm from cognitive sciences that is based on the principle of free energy. Based on this paradigm, the paper argues that even non-modular psychological processes can be computationally analyzed and algorithmically implemented. The conclusion of the paper is that, at least under the assumption that the func- tion of the mind is to minimize free energy, Marr’s levels of explanation can be successfully used as a general framework for understanding psychological processes at different levels of description. (shrink)

Progress in the last few decades in what is widely known as “Chaos Theory” has plainly advanced understanding in the several sciences it has been applied to. But the manner in which such progress has been achieved raises important questions about scientific method and, indeed, about the very objectives and character of science. In this presentation, I hope to engage my audience in a discussion of several of these important new topics.

The biomedical literature makes extensive use of the concept of a genetic program. So far, however, the nature of genetic programs has received no satisfactory elucidation from the standpoint of computer science. This unsettling omission has led to doubts about the very existence of genetic programs, on the grounds that gene regulatory networks lack a predetermined schedule of execution, which may seem to contradict the very idea of a program. I show, however, that we can make perfect sense of (...) genetic programs, if only we abandon the preconception that all computers have a von Neumann architecture. Instead, genetic programs instantiate the computational architecture of Post–Newell Production Systems. That is, genetic programs are unordered sets of conditional instructions, instructions that fire independently when their conditions are matched. For illustration I present a paradigm Production System that regulates the functioning of the well-known lac operon of E. coli. On close reflection it turns out that not only genes, but also proteins encode instructions. I propose, therefore, to rename genetic programs to biomolecular programs. Biomolecular and/or genetic programs, and the cellular computers than run them, are to be understood not as von Neumann computers, but as Post–Newell production systems. (shrink)

The chapter outlines an abstract theoretical framework that is currently (re-)emerging in the course of a theoretical convergence of several disciplines. In the first section, the fundamental problem of perception theory is formulated, namely, the generation, by the perceptual system, of meaningful categories from physicogeometric energy patterns. In the second section, it deals with basic intuitions and assumptions underlying what can be regarded as the current Standard Model of Perceptual Psychology and points out why this model is profoundly inadequate for (...) dealing with the fundamental problem of perception theory. In the third section, it discusses a level of analysis that promises to be fruitful for dealing, in conformity with established procedures of the natural sciences, with the problem of perceptual “meaning” and the problem of what constitutes a “perceptual object.” In the fourth section, it outlines a theoretical perspective on basic principles of the perceptual system which centers on the notions of complex data types and conceptual forms, and draws an entirely different theoretical picture of the role of the sensory input than traditional accounts. The final section focusses on the issue of material qualities and discusses, within the general theoretical framework outlined, some observations and results on the perception of certain material properties, namely, lustrous and glassy appearances. (shrink)

Scientists depend on complex computational systems that are often ineliminably opaque, to the detriment of our ability to give scientific explanations and detect artifacts. Some philosophers have s...

Emergence is typically discussed in the context of mental properties or the properties of the natural sciences, and accounts of emergence within these contexts tend to look a certain way. The emergent property is taken to emerge instantaneously out of, or to be proximately caused by, complex interaction of colocated entities. Here, however, I focus on the properties instantiated by the elements of certain systems discussed in social ontology, such as being a five-dollar bill or a pawn-movement, and I (...) suggest that these properties emerge in a distinctive way. They emerge in part because of a system that is far beyond and typically before the object that instantiates them. I characterize how emergence occurs in these cases, juxtaposing it with how emergence is typically discussed. I then consider whether their emergence is best framed as weak or strong as these notions are characterized in the literature, and I reveal what debates are central to answering this question. Though I will not resolve these debates, I do show a collection of views that would vindicate these properties as strongly emergent and downwardly causing. (shrink)

Since the nineteen fifties many social theorists, religion specialists, and theologians have turned to general systems theory for insight into the nature of religion and its expressions. As an interdisciplinary perspective introduced by the biologist Ludwig von Bertalanffy and developed by the philosopher Ervin Laszlo and others, systems theory seeks common patterns of organization throughout the natural and cultural worlds. Because of its high level of generality, expressed in the relational principles of integration, adaptation, emergence, and hierarchy, (...) class='Hi'>systems theory attempts to transcend artificial boundaries separating the sciences and the humanities. Advocates have claimed its value in interpreting a broad range of religious phenomena, including Christian theology and ethics, and Buddhist metaphysics and meditation. ;Religious studies has long struggled to integrate the competing contributions of the social sciences and phenomenology. A mediating proposal came in 1968 with Robert Bellah's cybernetic-systems theory of religion . An account of the common origins of systems theory and religious studies in nineteenth century thought , and a survey of representative literature between 1950 and 1985 , introduce a critique if specific methodological issues. ;The problem of functionalism is reinterpreted in terms of the adaptive self-regulation of open systems, and illustrated by three cybernetic theories of religion . The problem of historicism is reinterpreted in terms of the emergent self-organization of open systems, and illustrated by Talcott Parsons' action theory of religion and the theories of religious evolution of Bellah and D. T. Campbell . Reductionism is reconceived as the heuristic relationship of theoretical constructs in a hierarchy of open systems, and illustrated by theological conceptions of nature and meaning . ;In conclusion, the systems principle of integration is applied to the problems of personalism and pluralism, and illustrated in the personality theories of Bertalanffy, Koestler, Laszlo, and others. A systems theory of religious consciousness is shown to encompass the findings of religious studies broadly conceived: phenomenology and hermeneutics, social scientific theory, history of religions, philosophy of religion, and systematic theology. (shrink)

This work addresses a broad range of questions which belong to four fields: computation theory, general philosophy of science, philosophy of cognitive science, and philosophy of mind. Dynamical system theory provides the framework for a unified treatment of these questions. ;The main goal of this dissertation is to propose a new view of the aims and methods of cognitive science--the dynamical approach . According to this view, the object of cognitive science is a particular set of (...) dynamical systems, which I call "cognitive systems". The goal of a cognitive study is to specify a dynamical model of a cognitive system, and then use this model to produce a detailed account of the specific cognitive abilities of that system. The dynamical approach does not limit a-priori the form of the dynamical models which cognitive science may consider. In particular, this approach is compatible with both computational and connectionist modeling, for both computational systems and connectionist networks are special types of dynamical systems. ;To substantiate these methodological claims about cognitive science, I deal first with two questions in two different fields: What is a computational system? What is a dynamical explanation of a deterministic process? ;Intuitively, a computational system is a deterministic system which evolves in discrete time steps, and which can be described in an effective way. In chapter 1, I give a formal definition of this concept which employs the notions of isomorphism between dynamical systems, and of Turing computable function. In chapter 2, I propose a more comprehensive analysis which is based on a natural generalization of the concept of Turing machine. ;The goal of chapter 3 is to develop a theory of the dynamical explanation of a deterministic process. By a "dynamical explanation" I mean the specification of a dynamical model of the system or process which we want to explain. I start from the analysis of a specific type of explanandum--dynamical phenomena--and I then use this analysis to shed light on the general form of a dynamical explanation. Finally, I analyze the structure of those theories which generate explanations of this form, namely dynamical theories. (shrink)

Application of the reliability of repairable systems on solving problems from constructing production systems takes an important place in the process of finding the optimal solution among the suggested system choices. The basic hypothesis when using the reliability of the repairable systems is that every machine is representing a component, a fact that is debatable when talking about technical sciences. However, considering the second assumption of the stationary process, the function of the availability is introduced. It represents (...) the measure between the reliability and the benefit of maintaining the components and the system as a whole one. An additional and the last reason for analyzing constructing machine as a whole one has an economic reason. From the aspect of the total cost and the capacity of the system, the function of the availability is catching more and more impact in the process of determinating the total cost in bill of quantities as the most important part of tender documents. Until former works, techno-economic optimisation usually ran over when choosing the system of the construction machines. In the work, there are shown the methodologies for gathering and analyzing the indicators of availabilities per unit of a company's machine park. The time of demission and reparation have been investigated among 34 components in the period of 6 years. Based on the obtained result for different conditions of machine exploitation and facilities, it is suggested the methodology of the future behaviour of the corresponding within the model optimization availability of constructing production system with the aim of eliminating extra criterion. The suggested model takes in consideration the total cost of the components when they are functional, and when they are not. This kind of approach enables the one who take choices decision of the height of profits, in the lenght of work in function of the projection of cash flow and managing with real indicators of functioning the system at the project level. Given the fact that the maintanance policy of machines is based on availability, and not on reliability of components, with the aim of maximizing the availability of different budget scenarios, a logical approach to the selection of the objective function in the terms of management of construction production systems is to minimize costs for a given availability of system constructing machinery is based on the use of historical data base with the values of the operational availability of components, conditions in which they function, in the process of forecasting the project availability for projects that follow. Ranking variant solutions is the result of the adopted function of the aim as a consequence due to enlargement methods of availability for serial parallel systems with the associated restrictions. For optimal system availability is taken a value that belongs to minimal total cost. However, it is predicted that after the end of the financial year, the real and projected indicators of system functions get compared to each other. Informational support to the proposed model is informational company system, which was built in the PHP programming language on the Linux software platform, and with data based in My SQL. The suggested model is tested on the system for the production and embedding bitumen bound materials on the specific project. Obtained results confirm the assumptions used in work. (shrink)

This paper is concerned with the construction of theories of software systems yielding adequate predictions of their target systems’ computations. It is first argued that mathematical theories of programs are not able to provide predictions that are consistent with observed executions. Empirical theories of software systems are here introduced semantically, in terms of a hierarchy of computational models that are supplied by formal methods and testing techniques in computer science. Both deductive top-down and inductive bottom-up approaches (...) in the discovery of semantic software theories are refused to argue in favour of the abductive process of hypothesising and refining models at each level in the hierarchy, until they become satisfactorily predictive. Empirical theories of computational systems are required to be modular, as modular are most software verification and testing activities. We argue that logic relations must be thereby defined among models representing different modules in a semantic theory of a modular software system. We exclude that scientific structuralism is able to define module relations needed in software modular theories. The algebraic Theory of Institutions is finally introduced to specify the logic structure of modular semantic theories of computational systems. (shrink)