网范文：“Complexity and Philosophy ” 复杂性科学是基于一种新的思维方式,形成鲜明对比,牛顿科学哲学的基础,基于还原论,决定论和客观知识。这篇哲学范文综述了历史发展的新世界观,关注其哲学基础。决定论是量子力学和混沌理论的挑战。系统理论取代了还原论，英语论文范文，整体论是基础的科学。控制论和后现代社会科学表明,知识本质上是主观的。这些发展是综合复杂性科学，英语论文范文，它的核心范式是多代理系统。代理是内在主观和不确定的环境和未来。
尽管不同的哲学家,尤其是后现代主义者,也表达了类似的想法,复杂性范式还需要完全同化的哲学。这将把一个新的旧哲学的相对主义等问题放到其他层面上。复杂性可能是我们现在社会的最基本的特征。随着科技和经济的进步使生产、运输和通信更高效,我们与更多的人和组织进行交流。下面的范文进行详述。
ABSTRACT
The science of complexity is based on a new way of thinking that stands in sharp contrast to the philosophy underlying Newtonian science, which is based on reductionism, determinism, and objective knowledge. This reviews the historical development of this new world view, focusing on its philosophical foundations. Determinism was challenged by quantum mechanics and chaos theory. Systems theory replaced reductionism by a scientifically based holism. Cybernetics and postmodern social science showed that knowledge is intrinsically subjective. These developments are being integrated under the header of “complexity science”. Its central paradigm is the multi-agent system. Agents are intrinsically subjective and uncertain about their environment and future, but out of their local interactions, a global organization emerges. Although different philosophers, and in particular the postmodernists, have voiced similar ideas, the paradigm of complexity still needs to be fully assimilated by philosophy. This will throw a new light on old philosophical issues such as relativism, ethics and the role of the subject.
Introduction
Complexity is perhaps the most essential characteristic of our present society. As technological and economic advances make production, transport and communication ever more efficient, we interact with ever more people, organizations, systems and objects. And as this network of interactions grows and spreads around the globe, the different economic, social, technological and ecological systems that we are part of become ever more interdependent. The result is an ever more complex "system of systems" where a change in any component may affect virtually any other component, and that in a mostly unpredictable manner. The traditional scientific method, which is based on analysis, isolation, and the gathering of complete information about a phenomenon, is incapable to deal with such complex interdependencies.
The emerging science of complexity (Waldrop, 1992; Cilliers, 1998; Heylighen, 1997) offers the promise of an alternative methodology that would be able tackle such problems. However, such an approach needs solid foundations, that is, a clear understanding and definition of the underlying concepts and principles (Heylighen, 2017). Such a conceptual framework is still sorely lacking. In practice, applications of complexity science use either very specialized, technical formalisms, such as network clustering algorithms, computer simulations and non-linear differential equations, or rather vaguely defined ideas and metaphors, such as emergence and “the edge of chaos”.
As such, complexity science is little more than an amalgam of methods, models and metaphors from a variety of disciplines rather than an integrated science. Yet, insofar that complexity science can claim a unified focus, it is to be found precisely in its way of thinking, which is intrinsically different from the one of traditional science (Gershenson & Heylighen, 2017). A basic function of philosophy is to analyse and criticise the implicit assumptions behind our thinking, whether it is based in science, culture or common sense. As such, philosophy can help us to clarify the principles of thought that characterise complexity science and that distinguish it from its predecessors. Vice versa, complexity theory can help philosophy solve some of its perennial problems, such as the origins of mind, organization or ethics. Traditionally, philosophy is subdivided into metaphysics and ontology—which examines the fundamental categories of reality, logic and epistemology—which investigates how we can know and reason about that reality, aesthetics and ethics.
Aesthetics and ethics link into the questions of value and meaning, which are usually considered to be outside the scope of science. The present will therefore start by focusing on the subjects that are traditionally covered by philosophy of science, i.e. the ontology and epistemology underlying subsequent scientific approaches. We will present these in an approximately historical order, starting with the most “classical” of approaches, Newtonian science, and then moving via the successive criticisms of this approach in systems science and cybernetics, to the emerging synthesis that is complexity science. We will then summarise the impact these notions have had in social science and especially (postmodern) philosophy, thus coming back to ethics and other issues traditionally ignored by (hard) science.
Newtonian science Until the early 20th century, classical mechanics, as first formulated by Newton and further developed by Laplace and others, was seen as the foundation for science as a whole. It was expected that the observations made by other sciences would sooner or later be reduced to the laws of mechanics. Although that never happened, other disciplines, such as biology, psychology or economics, did adopt a general mechanistic or Newtonian methodology and world view. This influence was so great, that most people with a basic notion of science still implicitly equate “scientific thinking” with “Newtonian thinking”. The reason for this pervasive influence is that the mechanistic paradigm is compelling by its simplicity, coherence and apparent completeness. Moreover, it was not only very successful in its scientific applications, but largely in agreement with intuition and common-sense.
Later theories of mechanics, such as relativity theory and quantum mechanics, while at least as successful in the realm of applications, lacked this simplicity and intuitive appeal, and are still plagued by paradoxes, confusions and multiple interpretations. The logic behind Newtonian science is easy to formulate, although its implications are subtle. Its best known principle, which was formulated by the philosopher-scientist Descartes well before Newton, is that of analysis or reductionism: to understand any complex phenomenon, you need to take it apart, i.e. reduce it to its individual components. If these are still complex, you need to take your analysis one step further, and look at their components.
Complexity and Relativism
If complexity theory ultimately argues for the incompleteness of knowledge, it becomes a target, just like postmodernism, for those accusing it of relativism. This is not a meaningful accusation and has led to a lot of fruitless debates (cf. Sokal’s hoax). The dismissal of positions which try to be conscious of their own limitations is often a macho, if not arrogant move, one which is exactly insensitive to the ethical dimension involved when we deal with complexity. Modest positions do not have to be weak ones (see Norris, 1997; Cilliers, 2017). The development of a theoretical position which moves beyond the dichotomy of relativism and foundationalism (two sides of the same coin) is vital (cf. Heylighen, 2017).
The intersection between complexity and postmodern philosophy could lead to both exciting and very useful research. One of the rewards of this approach is that it allows insights from both the natural and the social sciences without one having to trump the other. Some Current Trends The contributions to the session on Philosophy and Complexity at the Complexity, Science, and Society conference (University of Liverpool, 2017), that was organized by one of us (Gershenson), and that we all participated in, provided a sample of current trends in the field. It was clear that concepts from complexity have not gone very deeply into philosophy, but the process is underway, since there are many open questions posed by scientific advances related to complexity, affecting especially epistemology and ethics. For example, research in life sciences demands a revaluation of our concept of 'life', while studies in cognitive sciences question our models of 'mind' and 'consciousness'.
The terminology introduced by complexity has already propagated, but not always with the best results. For example, the concept of emergence is still not well understood, a situation fuelled by the ignorant abuse of the term, although it is slowly being demystified. An important aspect of complex adaptive systems that is currently influencing philosophy is that of evolution. The dynamism introduced by cybernetics and postmodernism has not yet invaded all its possible niches, where remnants of reductionism or dualism remain. Philosophy no longer is satisfied by explaining why something is the way it is, but it needs to address the question of how it got to be that way. Conclusion For centuries, the world view underlying science has been Newtonian. The corresponding philosophy has been variously called reductionism, mechanicism or modernism. Ontologically, it reduces all phenomena to movements of independent, material particles governed by deterministic laws. Epistemologically, it holds the promise of complete, objective and certain knowledge of past and future. However, it ignores or even denies any idea of value, ethics, or creative processes, describing the universe as merely a complicated clockwork mechanism.
Over the past century, various scientific developments have challenged this simplistic picture, gradually replacing it by one that is complex at the core. First, Heisenberg’s uncertainty principle in quantum mechanics, followed by the notion of chaos in non-linear dynamics, showed that the world is intrinsically unpredictable. Then, systems theory gave a scientific foundation to the ideas of holism and emergence. Cybernetics, in parallel with postmodern social science, showed that knowledge is intrinsically subjective. Together with the theories of self-organization and biological evolution, they moreover made us aware that regularity or organization is not given, but emerges dynamically out of a tangle of conflicting forces and random fluctuations, a process aptly summarized as “order out of chaos” (Prigogine & Stengers, 1984). These different approaches are now starting to become integrated under the heading of “complexity science”.
Its central paradigm is the multi-agent system: a collection of autonomous components whose local interactions give rise to a global order. Agents are intrinsically subjective and uncertain about the consequences of their actions, yet they generally manage to self-organize into an emergent, adaptive system. Thus, uncertainty and subjectivity should no longer be viewed negatively, as the loss of the absolute order of mechanicism, but positively, as factors of creativity, adaptation and evolution. Although a number of (mostly postmodern) philosophers have expressed similar sentiments, the complexity paradigm still needs to be assimilated by academic philosophy. This may not only help philosophy solve some of its perennial problems, but help complexity scientists become more aware of the foundations and implications of their models.()
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