The task of axiomatizing physical theories has attracted, in recent years, some interest among both empirical scientists and logicians. However, the axiomatizations produced by either one of these two groups seldom appear satisfactory to the members of the other. It is the purpose of this paper to develop an approach that will satisfy the criteria of both, hence permit us to construct axiomatizations that will meet simultaneously the standards and needs of logicians and of empirical scientists.

The ability of an agent to overcome limitations caused by complexity can be identified with intelligence. Yet, the study of complexity is dominated by the issues not really associated with authentic intelligence. In search of the methods to overcome limitations of complexity it is necessary to find a sufficiently general conceptual framework for its study, to identify its characteristics and sources, and then to explore alternatives to the currently used methods. The present paper is using for this purpose the conceptual (...) framework of information, its integration, and dynamics developed by the author in his earlier publications. Using this framework, complexity is characterized in both quantitative and qualitative ways, and in both static and dynamic perspectives. The main objective is to propose an approach to transcending limitations of complexity through reverse engineering of the effectiveness in overcoming complexity by natural, living organisms. Since the most striking characteristic of life is its hierarchic organization, the use of multi-level hierarchic information systems in information processing is explored. Theoretical design of such multi-level systems becomes possible with the use of generalized Turing machines as components performing concurrent computation on all levels of the hierarchy. (shrink)

The traditional sciences have always had trouble with ambiguity. To overcome this barrier, ‘science’ has imposed “enabling constraints”—hidden assumptions which are given the status of ceteris paribus. Such assumptions allow ambiguity to be bracketed away at the expense of transparency. These enabling constraints take the form of uncritically examined presuppositions, which we refer to throughout the article as “uceps.” The meanings of the various uceps are shown via their applicability to the science of climate change. Second order science examines variations (...) in values assumed for these uceps and looks at the resulting impacts on related scientific claims. Second order science reveals hidden issues, problems and assumptions which all too often escape the attention of the practicing scientist. This article lays out initial foundations for second order science, its ontology, methodology, and implications. (shrink)

Realism concerning a given subject-matter is characterised as a semantic doctrine with metaphysical consequences, namely as the adoption, for the relevant class of statements, of a truth-conditional theory of meaning resting upon the classical two-valued semantics. it is argued that any departure from classical semantics may, though will not necessarily, be seen as in conflict with some variety of realism. a sharp distinction is drawn between the rejection of realism and the acceptance of a reductionist thesis; though intimately related, neither (...) entails the other. realism is to be classified as "naive", "semi-naive" or "sophisticated": the first of these involves an all but unintelligible epistemological component. (shrink)

In this Editorial note, Guest Editors introduce the theme of the Special Issue of the journal Philosophies, titled Contemporary Natural Philosophy and Philosophies.