I love information upon all subjects that come in my way, and especially upon those that are most important. Thus boldly declares Euphranor, one of the defenders of Christian faith in Berkley’s Alciphron (Berkeley, (1732), Dialogue 1, Section 5, Paragraph 6/10). Evidently, information has been an object of philosophical desire for some time, well before the computer revolution, Internet or the dotcompandemonium (see for example Dunn (2001) and Adams (2003)). Yet what does Euphranor love, exactly? What is (...) class='Hi'>information? The question has received many answers in different fields. Unsurprisingly, several surveys do not even converge on a single, unified definition of information (see for example Braman 1989, Losee (1997), Machlup and Mansfield (1983), Debons and Cameron (1975), Larson and Debons (1983)). (shrink)

Looks into evaluation of information provision probability from different sources, based on use of linguistic variables. Formation of functions appurtenant for its unclear variables provides for adoption of decisions by the decision maker, in conditions of nonprobabilistic equivocation. The development of market relations in Ukraine increases the independence and responsibility of enterprises in justifying and making management decisions that ensure their effective, competitive activities. As a result of the analysis, it is determined that the condition of economic facilities can (...) be described and determined by the decision-maker, in the presence of the necessary information. The confidence of the decision-maker in the information received is different and the decisions made have a correspondingly different level of information risk. It is important to substantiate the procedure for assessing the numerical extent of information risk in decision-making based on the information obtained in conditions of uncertainty. The use of a linguistic variable in the processing of expert data presented in the form of a matrix of binary relations of values of the membership function, which allowed to move to further processing of knowledge to support decision-making in the management of industrial, commercial, financial and other activities. As a mathematical model for estimating the numerical measure of information risk when making decisions based on the information obtained in conditions of non-stochastic uncertainty, a model has been developed to model natural language uncertainties, which differs from existing ones by formalizing knowledge taking into account uncertainty of input information. Making such a clear decision in a fuzzy environment has appropriate values of effectiveness and risk. The paper proposes all the functions and accessories of indicators of both quantitative nature and qualitative nature to bring their values in the field of definition to one scale. Then the indicator of the effectiveness of decision-making will be a measure of the clarity of the cross-section of fuzzy subsets, which correspond to the introduced indicators of information risk. The condition of economic facilities can be described and determined by the decision-maker, if the necessary information is available. Decision-making on thenumerical measure of information risk must be determined by a set of basic indicators, which can be both quantitative and qualitative in nature. Predictive values of indicators should be determined in conditions of nonstochastic uncertainty. In this case, the indicators of a quantitative nature can be determined by fuzzy triangular numbers, which implement a high level of confidence in the subjective judgments of experts. Indicators of qualitative nature should be presented in linguistic variables. The values of the indicators of qualitative nature that are predicted must be considered for all fuzzy variable terms-sets of linguistic variables introduced into consideration. For any fuzzy variable, the introduction to the consideration of a clear set of values as carriers of the α-level of its membership function allows to reduce to a single interpretation of the predicted values of indicators of quantitative and qualitative nature in terms of non-stochastic uncertainty. (shrink)

In Posterior Analytics 71b9 12, we find Aristotle’s definition of scientific knowledge. The definiens is taken to have only two informative parts: scientific knowledge must be knowledge of the cause and its object must be necessary. However, there is also a contrast between the definiendum and a sophistic way of knowing, which is marked by the expression “kata sumbebekos”. Not much attention has been paid to this contrast. In this paper, I discuss Aristotle’s definition paying due attention to (...) this contrast and to the way it interacts with the two conditions presented in the definiens. I claim that the “necessity” condition ammounts to explanatory appropriateness of the cause. (shrink)

This paper defines Wokeism with an empirical method for the academic definition of an oppressor, as currently there is no authoritative definition of either in academia. This is a novel definition as academic social science defines an oppressor subjectively induced from theory. This paper proposes an empirical framework to define and identify “oppressors” using measurable criteria grounded in the four instruments of power: physical force, political power, economic power, and informational power. Unlike prevailing approaches within academia, which (...) often apply the label of "oppressor" based on subjective perceptions, this framework emphasizes objective, verifiable criteria. It seeks to clarify complex power dynamics and offers a standardized method for evaluating oppressive behavior, aiming to promote accountability and reduce the misuse of labels. This framework holds particular relevance in public discourse and policy-making, enhancing the credibility and rigor of social science research on social justice, power, and what entities are oppressors, which are not, and which previously accused oppressors from academia can now be vindicated. (shrink)

The paper investigates the ethics of information transparency (henceforth transparency). It argues that transparency is not an ethical principle in itself but a pro-ethical condition for enabling or impairing other ethical practices or principles. A new definition of transparency is offered in order to take into account the dynamics of information production and the differences between data and information. It is then argued that the proposed definition provides a better understanding of what sort of (...) class='Hi'>information should be disclosed and what sort of information should be used in order to implement and make effective the ethical practices and principles to which an organisation is committed. The concepts of “heterogeneous organisation” and “autonomous computational artefact” are further defined in order to clarify the ethical implications of the technology used in implementing information transparency. It is argued that explicit ethical designs, which describe how ethical principles are embedded into the practice of software design, would represent valuable information that could be disclosed by organisations in order to support their ethical standing. (shrink)

Davies presents the reader with a sterling review of the literature--the recent history of the interest in defining "art" through the writings of Anglo-American philosophers that follow Morris Weitz' well-known 1956 essay, "The Role of Theory in Aesthetics"--and a stimulating discussion of the role of conventions in the making and appreciating of contemporary art. His emphasis on the social nature of art leads one to wonder how other recent inquiries into the multilayered contextually of the artistic enterprise might fare under (...) his perusal, for example, feminist critiques of traditional definitions of "art," challenges to the elitist makeup of the Artworld, . . . and opposition to his very choice of paradigms: in addition to Duchamp, the "hard cases" include works by John Cage, Andy Warhol, Olivier Messiaen, Jorge Luis Borges, and Gerald Hoffnung. Definitions of Art is essential reading for anyone interested in the history of aesthetics and as it informs the current dialectic on art. (shrink)

One of our major advances this year is the informational entropy-based definition of value, whose mechanism and explanation are provided in the short research note. Since its inception, the concept has enabled us to efficiently perform some research tasks that would be impossible otherwise. -/- However, the above-mentioned short paper may need some kind of guidance so that someone new to it can more readily apply the concept. That’s why this post is written.

This paper aims to establish several interconnected points. First, a particular interpretation of the mathematical definition of information, known as the causal interpretation, is supported largely by misunderstandings of the engineering context from which it was taken. A better interpretation, which makes the definition and quantification of information relative to the function of its user, is outlined. The first half of the paper is given over to introducing communication theory and its competing interpretations. The second half (...) explores three consequences of the main thesis. First, a popular claim that the quantification of information in a signal is irrelevant for the meaning of that signal is exposed as fallacious. Second, a popular distinction between causal and semantic information is shown to be misleading, and I argue it should be replaced with a related distinction between natural and intentional signs. Finally, I argue that recent empirical work from microbiology and cognitive science drawing on resources of mathematical communication theory is best interpreted by the functional account. Overall, a functional approach is shown to be both theoretically and empirically well-supported. (shrink)

The common use of Shannon’s information, specified for the needs of telecommunications, gives rise to many misunderstandings outside of this context. (e.g. in conceptions of such well-known theorists as C.F. Weizsäcker and J. A. Wheeler). This article shows that the terms of the general definition of information meet the structural information, and Shannon’s information is a special case of it. Similarly, complexity is misunderstood today as exemplified by the concepts of reputable computer scientists, such as (...) S. Lloyd, S. Wolfram and J. Schmidhuber. These theorists use an algorithmic definition of complexity and the so-called logical depth, neither of which meets the intuitive criterion of complexity. Hence, their misconceptions of beauty, art and the universe. It will be shown that the intuitive criterion is met by Abstract Complexity Definition. This definition also fulfils the criterion for a general complexity definition, as it defines complexity of the most general/abstract structure of our reality, that is, binary structure. It also explains such fundamental issues of information theory as the information–energy relationship and the value of information, which are still discussed and need to be clarified. (shrink)

[I argue that a precise definition of emotions is neither necessary nor possible prior to empirical research on emotions. It is not necessary because all that is needed for for fruitful research and successful communication is a working definition of emotions, a description that allows to roughly demarcate the class of emotions. It is not possible because precise emotion definitions are real definitions, empirical claims about the essence of emotions. These claims about the nature of emotion are always (...) formulated against the background of a theory of emotion generation, whose truth they presuppose. The claim that emotions are syndromes of mental and behavioral states is such a theoretical definition of emotion. It is put into question by the finding of low correlations between the proposed syndrome components.] . (shrink)

In this article, the results of conceptualization of the definition of mind as an object of interdisciplinary applied research are described. The purpose of the theoretical analysis is to generate a methodological discourse suitable for a functional understanding of the mind in the context of the problem of natural language processing as one of the components of developments in the field of artificial intelligence. The conceptual discourse was realized with the help of the author's method of structural-ontological analysis, and (...) developed in the mainstream of the system-methodological tradition of the school of G.P. Shchedrovitsky and intended for descriptive research of subject areas of interdisciplinary objects of scientific study. As a result of the structural and ontological analysis of the super-system, the relevant place and role of the directly studied system (mind) are determined, and its primary process and material are localized and structural and functional connections are described. At the basic level, the mind is conceptualized as an energy process unfolding in a spatio-temporal environment and accompanied by archetypal structuring of neural impulses into images. The genesis of the system is separately analyzed by constructing a structural-ontological matrix that reflects the initial stage of the development of the mind. The primary process is concretized with the help of hetero- and homeostatic dichotomy, and also the most significant features of the consistent transformation of the material of the system and its ascent to verbal morphology are described. The structural-ontological comparison of the functioning of the verbal intelligence with the preverbal level has been carried out. The transformation of neural impulses of needs into words, as verbal units fixing semiotic values is analyzed. Structural-ontological connections that determine the reactive and prospective characteristics of the functioning of the system are disclosed. The position of the chronological primacy of "semiotic readiness" for language with respect to the debut of the latter as an information-sign model of the environment is argued. The hypothesis of domination at the initial stage of the development of the mind of exopsychic functions over endopsychic ones is formulated. The theoretical substantiation of the hypothesis of the inevitability of the ontology of language in the functional understanding of the mind is given, corresponding structural and ontological arguments are given, including those based on the ideas about the information relationship between affects and needs, according to the views of P.V. Simonov. The arguments are presented in favor of the non-alternative methodology of A. Turing in studies of artificial intelligence. (shrink)

In this work, author evaluated past theories and perspectives behind the definitions of science and/or branches of science. Also some of the philosophers of science and their specific philosophical interests were expressed. Author considered some type of interactions between some disciplines to determine, to solve the philosophical/scientific problems and to define the possible solutions. The purposes of this article are: (i) to define new synthesis method, (ii) to define new perspective for the philosophy of science, (iii) to define relation between (...) new philosophy perspective and philosophy of science, (iv) to define and organize name, number, relations, and correct structure between special science branches and philosophy of science, (v) to define necessary and sufficient number of branches for philosophy of science, (vi) to define and express the importance and place of new philosophy of science perspective in the new system, (vii) to extend the definition/limits of philosophy of science, (viii) to re-define meanings of some philosophical/scientific theories, (ix) to define systematic solution for the conflicts, problems, confusions about philosophy of science, sciences and branches of science, (x) to define new branches of science, (xi) to re-construct branches and hierarchy of science, (xii) to define new theories about science and branches of science. Author considered R-Synthesis as a method for the evaluation of the philosophy, philosophy of science, sciences and branches of science. This R-Synthesis includes evaluation of eight categories of general/specific perspective, 21-dimensions, and 12 general subjects (with related scope and contents) for the past 12,000 years. It is a kind of synthesis of science and non-science, physical science and non-physical science, religious science and non-religious science, and others. In this article, author defined 27 possible definitive/certain result cases for this new synthesis. Author defined the possible formation stages shortly to express new disciplines, new constructional and/or complementary theories. These theories are considered to define 21 major effective disciplines. New philosophy perspective is defined (R-Philosophy) shortly. New perspective and sub branches are defined for the philosophy of science. Major sciences are defined due to new basic philosophies. 42-basic components are defined for each science branch. New and/or re-constructed sciences, branches of science, basic sciences, and new hierarchy of science are defined with figure. Electromagnetic sciences, information sciences, and system sciences are defined specifically. Hybrid Sciences, New Era Science, and Ideal Scientific System are defined with general/specific figure. Relation between the some old branches and new branches of science was expressed generally due to new perspective of philosophy of science. (shrink)

It was shown recently that information is the central concept which it is to be considered to understand consciousness and its properties. Arguing that consciousness is a consequence of the operational activity of the informational system of the human body, it was shown that this system is composed by seven informational components, reflected in consciousness by corresponding cognitive centers. It was argued also that consciousness can be connected to the environment not only by the common senses, but also by (...) a special connection pole to the bipolar properties of the universe, allowing to explain the associated phenomena of the near-death experiences and other special phenomena. Starting from the characteristics of this model, defined as the Informational Model of Consciousness and to complete the info-communication panorama, in this paper it is analyzed the info-connectivity of the informational system with the body itself. The brain areas where the activity of each informational component are identified, and a definition of consciousness in terms of information is proposed. As the electrical connectivity by means of the nervous system was already proved, allowing the application of the analysis and developing tools of the information science, a particular attention is paid to the non-electrical mechanisms implied in the internal communication. For this, it is shown that the key mechanisms consists in embodiment/disembodiment processes of information during the inter and intra communication of the cells. This process can be modeled also by means of, and in correlation with specific concepts of the science and technology of information, referred to network communication structures, and is represented by epigenetic mechanisms, allowing the acquired trait transmission to the offspring generation. From the perspective of the informational model of consciousness, the human organism appears therefore as a dynamic reactive informational system, actuating in correlation with matter for adaptation, by embodiment/disembodiment processes of information. (shrink)

In this article, author evaluated past/present perspectives about philosophy and branches of philosophy due to historical period, religious perspective, and due to their organized categories/branches or areas. Some types of interactions between some disciplines are given as an example. The purpose of this article is, to solve problems related with philosophy and past branches of philosophy, to define new philosophy perspective in the new system, to define new questions and questioning about philosophy or branches of philosophy, to define new or (...) re-constructed branches of philosophy, to define the relations between the philosophy branches, to define good and/or correct structure of philosophy and branches of philosophy, to extend the definition/limits of philosophy, others. Author considered R-Synthesis as a method for the evaluation of the philosophy and related past branches of philosophy. This R-Synthesis includes general/specific perspective with eight categories, 21-dimensions, and twelve general subjects for the past 12,000 years. It is a kind of synthesis of supernaturalism and naturalism, physics and metaphysics, others. In this article, author expressed 27 possible definitive/certain result cases of the new synthesis and defined the possible formation stages to express new theories, new disciplines, theory of interaction, theory of relation, hybrid theory, and others as constructional and/or complementary theories. These theories are considered for 21 major effective disciplines which are defined for a country and for the world. New philosophy perspective, branches of philosophy, and aims/purposes of R-Philosophy are defined to organize many inquiries about the name, number, and relation between special subject “X” and “philosophy of X” in some manner. This new perspective includes necessary and sufficient number of philosophy branches, and so it limits the number of “philosophy of X” in the philosophical system. New Era Philosophy is defined with its sub branches, its constructional philosophies, and with its 8D hybrid philosophy perspective. Ideal Philosophical System is defined with general/specific figure. Some of the new and/or re-constructed branches of philosophy explained with the new defined set of questions, new sub branches and constructional philosophies. Integration of the past/present branches of philosophy into the ideal philosophical system is explained generally. Philosophical interests of the some past philosophers and their relations with the ideal philosophical system expressed with table. (shrink)

This paper connects information with computation and cognition via concept of agents that appear at variety of levels of organization of physical/chemical/cognitive systems – from elementary particles to atoms, molecules, life-like chemical systems, to cognitive systems starting with living cells, up to organisms and ecologies. In order to obtain this generalized framework, concepts of information, computation and cognition are generalized. In this framework, nature can be seen as informational structure with computational dynamics, where an (info-computational) agent is needed (...) for the potential information of the world to actualize. Starting from the definition of information as the difference in one physical system that makes a difference in another physical system – which combines Bateson and Hewitt’s definitions, the argument is advanced for natural computation as a computational model of the dynamics of the physical world, where information processing is constantly going on, on a variety of levels of organization. This setting helps us to elucidate the relationships between computation, information, agency and cognition, within the common conceptual framework, with special relevance for biology and robotics. (shrink)

N. Wiener's negative definition of information is well known: it states what information is not. According to this definition, it is neither matter nor energy. But what is it? It is shown how one can follow the lead of dialectical logic as expounded by G.W.F. Hegel in his main work -- "The Science of Logic" -- to answer this and some related questions.

In this short paper, we show that a popular view in information science, information-as-thing, fails to account for a common example of information that seems physical. We then demonstrate how the distinction between types and tokens, recently used to analyse Shannon information, can account for this same example by viewing information as abstract, and discuss existing definitions of information that are consistent with this approach. -/- Dans ce court article nous montrons qu'une vision populaire (...) en sciences de l'information, l'information en tant qu’une chose, échoue à rendre compte d'un exemple commun d'information qui semble physique. Nous démontrons ensuite comment la distinction type/token, utilisée récemment pour analyser l'information de Shannon, peut rendre compte de ce même exemple en considérant l'information comme abstraite, et nous discutons des définitions existantes de l’information qui sont compatibles avec cette approche. (shrink)

The explicit history of the “hidden variables” problem is well-known and established. The main events of its chronology are traced. An implicit context of that history is suggested. It links the problem with the “conservation of energy conservation” in quantum mechanics. Bohr, Kramers, and Slaters (1924) admitted its violation being due to the “fourth Heisenberg uncertainty”, that of energy in relation to time. Wolfgang Pauli rejected the conjecture and even forecast the existence of a new and unknown then elementary particle, (...) neutrino, on the ground of energy conservation in quantum mechanics, afterwards confirmed experimentally. Bohr recognized his defeat and Pauli’s truth: the paradigm of elementary particles (furthermore underlying the Standard model) dominates nowadays. However, the reason of energy conservation in quantum mechanics is quite different from that in classical mechanics (the Lie group of all translations in time). Even more, if the reason was the latter, Bohr, Cramers, and Slatters’s argument would be valid. The link between the “conservation of energy conservation” and the problem of hidden variables is the following: the former is equivalent to their absence. The same can be verified historically by the unification of Heisenberg’s matrix mechanics and Schrödinger’s wave mechanics in the contemporary quantum mechanics by means of the separable complex Hilbert space. The Heisenberg version relies on the vector interpretation of Hilbert space, and the Schrödinger one, on the wave-function interpretation. However the both are equivalent to each other only under the additional condition that a certain well-ordering is equivalent to the corresponding ordinal number (as in Neumann’s definition of “ordinal number”). The same condition interpreted in the proper terms of quantum mechanics means its “unitarity”, therefore the “conservation of energy conservation”. In other words, the “conservation of energy conservation” is postulated in the foundations of quantum mechanics by means of the concept of the separable complex Hilbert space, which furthermore is equivalent to postulating the absence of hidden variables in quantum mechanics (directly deducible from the properties of that Hilbert space). Further, the lesson of that unification (of Heisenberg’s approach and Schrödinger’s version) can be directly interpreted in terms of the unification of general relativity and quantum mechanics in the cherished “quantum gravity” as well as a “manual” of how one can do this considering them as isomorphic to each other in a new mathematical structure corresponding to quantum information. Even more, the condition of the unification is analogical to that in the historical precedent of the unifying mathematical structure (namely the separable complex Hilbert space of quantum mechanics) and consists in the class of equivalence of any smooth deformations of the pseudo-Riemannian space of general relativity: each element of that class is a wave function and vice versa as well. Thus, quantum mechanics can be considered as a “thermodynamic version” of general relativity, after which the universe is observed as if “outside” (similarly to a phenomenological thermodynamic system observable only “outside” as a whole). The statistical approach to that “phenomenological thermodynamics” of quantum mechanics implies Gibbs classes of equivalence of all states of the universe, furthermore re-presentable in Boltzmann’s manner implying general relativity properly … The meta-lesson is that the historical lesson can serve for future discoveries. (shrink)

In “Toward an Ontology of Commercial Exchange” [11], we proposed human readable definitions for terms that are central to an ontology of commercial exchange. This paper furthers that project in two ways. First, the definitions have been modified to be compatible with the Common Core Ontologies (CCO). CCO is used in a wide variety of domains including the industrial and military domains. Having a commerce ontology compatible with CCO allows data about the exchange of goods relevant to those domains to (...) be tagged with compatible ontologies. Second, we propose preliminary formalizations of these definitions, with the aim of informing the creation of an ontology which can be used to assist in reasoning over businessrelated data. (shrink)

The concept of formal transcendentalism is utilized. The fundamental and definitive property of the totality suggests for “the totality to be all”, thus, its externality (unlike any other entity) is contained within it. This generates a fundamental (or philosophical) “doubling” of anything being referred to the totality, i.e. considered philosophically. Thus, that doubling as well as transcendentalism underlying it can be interpreted formally as an elementary choice such as a bit of information and a quantity corresponding to the number (...) of elementary choices to be defined. This is the quantity of information defined both transcendentally and formally and thus, philosophically and mathematically. If one defines information specifically, as an elementary choice between finiteness (or mathematically, as any natural number of Peano arithmetic) and infinity (i.e. an actually infinite set in the meaning of set theory), the quantity of quantum information is defined. One can demonstrate that the so-defined quantum information and quantum information standardly defined by quantum mechanics are equivalent to each other. The equivalence of the axiom of choice and the well-ordering “theorem” is involved. It can be justified transcendentally as well, in virtue of transcendental equivalence implied by the totality. Thus, all can be considered as temporal as far anything possesses such a temporal counterpart necessarily. Formally defined, the frontier of time is the current choice now, a bit of information, furthermore interpretable as a qubit of quantum information. (shrink)

One of the basic principles of the general definition of information is its rejection of dataless information, which is reflected in its endorsement of an ontological neutrality. In general, this principles states that “there can be no information without physical implementation” (Floridi (2005)). Though this is standardly considered a commonsensical assumption, many questions arise with regard to its generalised application. In this paper a combined logic for data and information is elaborated, and specifically used to (...) investigate the consequences of restricted and unrestricted data-implementation-principles. (shrink)

Learning from contemporary natural, formal, and social sciences, especially from current biology, as well as from humanities, particularly contemporary philosophy of nature, requires updates of our old definitions of cognition and intelligence. The result of current insights into basal cognition of single cells and evolution of multicellular cognitive systems within the framework of extended evolutionary synthesis (EES) helps us better to understand mechanisms of cognition and intelligence as they appear in nature. New understanding of information and processes of physical (...) (morphological) computation contribute to novel possibilities that can be used to inspire the development of abiotic cognitive systems (cognitive robotics), cognitive computing and artificial intelligence. (shrink)

Definition of the problem The umbrella term “explicability” refers to the reduction of opacity of artificial intelligence (AI) systems. These efforts are challenging for medical AI applications because higher accuracy often comes at the cost of increased opacity. This entails ethical tensions because physicians and patients desire to trace how results are produced without compromising the performance of AI systems. The centrality of explicability within the informed consent process for medical AI systems compels an ethical reflection on the trade-offs. (...) Which levels of explicability are needed to obtain informed consent when utilizing medical AI? Arguments We proceed in five steps: First, we map the terms commonly associated with explicability as described in the ethics and computer science literature, i.e., disclosure, intelligibility, interpretability, and explainability. Second, we conduct a conceptual analysis of the ethical requirements for explicability when it comes to informed consent. Third, we distinguish hurdles for explicability in terms of epistemic and explanatory opacity. Fourth, this then allows to conclude the level of explicability physicians must reach and what patients can expect. In a final step, we show how the identified levels of explicability can technically be met from the perspective of computer science. Throughout our work, we take diagnostic AI systems in radiology as an example. Conclusion We determined four levels of explicability that need to be distinguished for ethically defensible informed consent processes and showed how developers of medical AI can technically meet these requirements. (shrink)

Based on Kolchinsky and Wolpert’s work on the semantics of autonomous agents, I propose an application of Mathematical Logic and Probability to model cognitive processes. In this work, I will follow Bateson’s insights on the hierarchy of learning in complex organisms and formalize his idea of applying Russell’s Type Theory. Following Weaver’s three levels for the communication problem, I link the Kolchinsky–Wolpert model to Bateson’s insights, and I reach a semantic and conceptual hierarchy in living systems as an explicative model (...) of some adaptive constraints. Due to the generality of Kolchinsky and Wolpert’s hypotheses, I highlight some fundamental gaps between the results in current Artificial Intelligence and the semantic structures in human beings. In light of the consequences of my model, I conclude the paper by proposing a general definition of knowledge in probabilistic terms, overturning de Finetti’s Subjectivist Definition of Probability. (shrink)

This article proposes a new interpretation of mutual information. We examine three extant interpretations of MI by reduction in doubt, by reduction in uncertainty, and by divergence. We argue that the first two are inconsistent with the epistemic value of information assumed in many applications of MI: the greater is the amount of information we acquire, the better is our epistemic position, other things being equal. The third interpretation is consistent with EVI, but it is faced with (...) the problem of measure sensitivity and fails to justify the use of MI in giving definitive answers to questions of information. We propose a fourth interpretation of MI by reduction in expected inaccuracy, where inaccuracy is measured by a strictly proper monotonic scoring rule. It is shown that the answers to questions of information given by MI are definitive whenever this interpretation is appropriate, and that it is appropriate in a wide range of applications with epistemic implications. _1_ Introduction _2_ Formal Analyses of the Three Interpretations _2.1_ Reduction in doubt _2.2_ Reduction in uncertainty _2.3_ Divergence _3_ Inconsistency with Epistemic Value of Information _4_ Problem of Measure Sensitivity _5_ Reduction in Expected Inaccuracy _6_ Resolution of the Problem of Measure Sensitivity _6.1_ Alternative measures of inaccuracy _6.2_ Resolution by strict propriety _6.3_ Range of applications _7_ Global Scoring Rules _8_ Conclusion. (shrink)

The paper interprets the concept “operator in the separable complex Hilbert space” (particalry, “Hermitian operator” as “quantity” is defined in the “classical” quantum mechanics) by that of “quantum information”. As far as wave function is the characteristic function of the probability (density) distribution for all possible values of a certain quantity to be measured, the definition of quantity in quantum mechanics means any unitary change of the probability (density) distribution. It can be represented as a particular case of (...) “unitary” qubits. The converse interpretation of any qubits as referring to a certain physical quantity implies its generalization to non-Hermitian operators, thus neither unitary, nor conserving energy. Their physical sense, speaking loosely, consists in exchanging temporal moments therefore being implemented out of the space-time “screen”. “Dark matter” and “dark energy” can be explained by the same generalization of “quantity” to non-Hermitian operators only secondarily projected on the pseudo-Riemannian space-time “screen” of general relativity according to Einstein's “Mach’s principle” and his field equation. (shrink)

To become more useful and efficient in sustaining the Earth's health, economics must undergo a paradigm shift in its thinking. From a humanistic perspective, humans should be the center of everything. However, from the standpoint of physics and the universe, this is not the case. As a species, having a planet among the millions in the universe where humans can survive and thrive is already a great fortune. Through this book, we also try to answer one of our long-standing questions: (...) why has economics learned so little from physics, the oldest and most rigorous academic discipline that studies nature? -/- Learning from the quantum and information theories, we also provide a new definition of value, which is expected to help economists relax assumptions and loosen established economic principles in order to change and evolve. The new definition is also expected to enable social scientists to address newly arising phenomena or events that are not accounted for by existing value systems, such as environmental crises, artificial intelligence (AI), and interdisciplinary information, more proactively and productively. (shrink)

To understand what ontologies do through their definitions, we propose a theoretical explanation of the functions of definitions in ontologies backed by empirical neuropsychological studies. Our goal is to show how these functions should motivate (i) the systematic inclusion of definitions in ontologies and (ii) the adaptation of definition content and form to the specific context of use of ontologies.

The article introduces the special issue dedicated to “The Philosophy of Information, Its Nature, and Future Developments.” It outlines the origins of the information society and then briefly discusses the definition of the philosophy of information, the possibility of reconciling nature and technology, the informational turn as a fourth revolution (after Copernicus, Darwin, and Freud), and the metaphysics of the infosphere.

Information and meaning exist around us and within ourselves, and the same information can correspond to different meanings. This is true for humans and animals, and is becoming true for robots. We propose here an overview of this subject by using a systemic tool related to meaning generation that has already been published (C. Menant, Entropy 2003). The Meaning Generator System (MGS) is a system submitted to a constraint that generates a meaningful information when it receives an (...) incident information that has a relation with the constraint. The content of the meaningful information is explicited, and its function is to trigger an action that will be used to satisfy the constraint of the system. The MGS has been introduced in the case of basic life submitted to a "stay alive" constraint. We propose here to see how the usage of the MGS can be extended to more complex living systems, to humans and to robots by introducing new types of constraints, and integrating the MGS into higher level systems. The application of the MGS to humans is partly based on a scenario relative to the evolution of body self-awareness toward self-consciousness that has already been presented (C. Menant, Biosemiotics 2003, and TSC 2004). The application of the MGS to robots is based on the definition of the MGS applied to robots functionality, taking into account the origins of the constraints. We conclude with a summary of this overview and with themes that can be linked to this systemic approach on meaning generation. (shrink)

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske‐Grice approach: meaningful and well‐formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is (...) incorrect because truth‐values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo‐information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo‐information. As a consequence, SDI is revised to include a necessary truth‐condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition. (shrink)

We propose here to clarify some of the relations existing between information and meaning by showing how meaningful information can be generated by a system submitted to a constraint. We build up definitions and properties for meaningful information, a meaning generator system and the domain of efficiency of a meaning (to cover cases of meaningful information transmission). Basic notions of information processing are used.

Looking out of Information Science (IS) it´s a dangerous attempt to compare this relative new science direct with Philosophy. Here you find a first circumspective trial of an investigation of the traditionally named “queen of science”, Philosophy, two thousand years old and - direct opposite - the only a half century old Information Science. For me it is till now not yet clear how to do this in a serious scientific manner. I worked in Applied Informatics for 30 (...) years and make Information Science since about 15 years. Here I dare to publish for first time the results. SOKRATES (469 – 399 b.Chr.), PLATON (428/27- 348/47 b.Chr.) und ARISTOTELES (384 - 322 b.Chr.) as inventors of our traditional occidental Philosophy, have founded the search of the sense of our Human Life, Thinking and Acting as an own science. They set the Joy of Life on top of their way of thinking. PLATON has separated this special new thinking from the „Sophists“ who had a very good public image too at his time. But they were thinking more about common business facts and knowledge only. Today we would call them manufacturer, qualified skilled workers or even bachelors of special sciences. Philosophy has (since over 20 centuries) till today first of all the smart and high duty to serve Religion and Ethics as mental, spirit- and language-grounded science-base. In other direction it was used to overthink our whole surrounding nature theoretically and completely by our best Human Mind. It´s our traditional science on our mental highest level. All sciences can be related by Philosophy. That´s possible by our human ability to Learn, Think, Understand and finally Know any interesting new fact. Where and how do we have now to integrate this new own science Information Science? We search consciously term-oriented and make an abstract science-theoretical comparison to find answers and definitions. (shrink)

This paper demonstrates the practical and philosophical strengths of adopting Luciano Floridi’s “general definition of information” (GDI) for use in the information sciences (IS). Many definitions of information have been proposed, but little work has been done to determine which definitions are most coherent or useful. Consequently, doubts have been cast on the necessity and possibility of finding a definition. In response to these doubts, the paper shows how items and events central to IS are (...) adequately described by Floridi’s conception of information, and demonstrates how it helps clarify the muddy theoretical framework resulting from the many previous definitions. To this end, it analyzes definitions, popular in IS, that conceive of information as energy, processes, knowledge, and physical objects. The paper finds that each of these definitions produces problematic or counterintuitive implications that the GDI suitably accounts for. It discusses the role of truth in IS, notes why the GDI is preferable to its truth-requiring variant, and ends with comments about the import of such a theory for IS research and practice. (shrink)

The common account of the analog vs digital distinction is based on features of physical systems, being related to the usage of continuous vs discrete supports respectively. It is proposed here to alternatively characterize the concepts of analog and digital as related to coding systems, of which a formal definition is given, by suggesting that the distinction refers to the strategy adopted to define the coding function: extensional in digital systems, isomorphic intensional in analog systems. This thesis is supported (...) by examples, in particular of analog systems exploiting discrete supports, and is discussed to explain why digital coding is currently so widespread in technological and social practice. (shrink)

The book Theory and Practice of Contrast completes, corrects and integrates the foundations of science and humanities, which include: theory of art, philosophy (aesthetics, epistemology, ontology, axiology), cognitive science, theory of information, theory of complexity and physics. Through the integration of these distant disciplines, many unresolved issues in contemporary science have been clarified or better understood, among others: defining impact (contrast) and using this definition in different fields of knowledge; understanding what beauty/art is and what our aesthetic preferences (...) depend on; deeper understanding of what complexity and information are in essence, and providing their general definitions. Complexity means integration, value and goodness - concepts that seem to be neglected today. The book also has a high degree of integration/complexity, although each chapter introduces a new issue. The last chapter: "Binary Model of the Universe" draws attention to the need for including in physics the analysis of our mind and the resulting new possibilities, which include the mentioned (digital) model of the universe. Despite the difficult issues raised here, this study is written in accessible language and may be interesting not only for scientists and academics. (shrink)

The paper justifies the following theses: The totality can found time if the latter is axiomatically represented by its “arrow” as a well-ordering. Time can found choice and thus information in turn. Quantum information and its units, the quantum bits, can be interpreted as their generalization as to infinity and underlying the physical world as well as the ultimate substance of the world both subjective and objective. Thus a pathway of interpretation between the totality via time, order, choice, (...) and information to the substance of the world is constructed. The article is based only on the well-known facts and definitions and is with no premises in this sense. Nevertheless it is naturally situated among works and ideas of Husserl and Heidegger, linked to the foundation of mathematics by the axiom of choice, to the philosophy of quantum mechanics and information. (shrink)

In 2014, John O’Keefe was awarded the Nobel Prize in Physiology or Medicine for his work on the hippocampus and its role in encoding map-like representations. His contributions were significantly influenced by Morris water maze studies. O’Keefe himself acknowledged the pivotal role of the Morris water maze, stating that it remains the preeminent behavioral assay for assessing hippocampal function. Indeed, thousands of researchers have turned to the Morris water maze for evidence about navigation abilities and the effects that stress, lesions, (...) pharmaceutical interventions, and more can have on them. This body of studies constitutes an important scientific enterprise. -/- This dissertation is about some of the philosophical dimensions of Morris water maze studies. Chapter 1 is about the different types of information states (including representational states) found across hypotheses about Morris water maze performance. Chapter 2 is about systematic task failures reported in Morris water maze studies. I argue these impose a constraint on what can count as an explanation (a good hypothesis) of task success. While this has the air of a chopping block for scientific hypotheses, I see things a little differently. In Chapter 3, I argue that satisfying the constraint is a formidable challenge for any hypothesis. One that should make researchers second-guess the concepts and strategies employed to explain the roles information states play in the maze task. Chapter 4 focuses on two spatial concepts. I argue that researchers working definitions for the spatial concepts of distal (far) and proximal (near) in maze studies are problematic. They are not ecologically valid, and so claims about them do not generalize to real-life navigation behaviors like migration or scavenging behaviors. Following this, I present alternative definitions in terms of neural information about visual cues. The neural information relevant to this account is non-conceptual, and so it provides a sketch of the ways in which information states can fruitfully contribute to explanations of rat success and failure while maintaining ecological validity. -/- To sum, this dissertation navigates important philosophical dimensions of Morris water maze studies, illustrating the challenges and opportunities involved in using information states to explain and understand animal navigation. (shrink)

The concept of quantum information is introduced as both normed superposition of two orthogonal sub-spaces of the separable complex Hilbert space and in-variance of Hamilton and Lagrange representation of any mechanical system. The base is the isomorphism of the standard introduction and the representation of a qubit to a 3D unit ball, in which two points are chosen. The separable complex Hilbert space is considered as the free variable of quantum information and any point in it (a wave (...) function describing a state of a quantum system) as its value as the bound variable. A qubit is equivalent to the generalization of ‘bit’ from the set of two equally probable alternatives to an infinite set of alternatives. Then, that Hilbert space is considered as a generalization of Peano arithmetic where any unit is substituted by a qubit and thus the set of natural number is mappable within any qubit as the complex internal structure of the unit or a different state of it. Thus, any mathematical structure being reducible to set theory is re-presentable as a set of wave functions and a subspace of the separable complex Hilbert space, and it can be identified as the category of all categories for any functor represents an operator transforming a set (or subspace) of the separable complex Hilbert space into another. Thus, category theory is isomorphic to the Hilbert-space representation of set theory & Peano arithmetic as above. Given any value of quantum information, i.e. a point in the separable complex Hilbert space, it always admits two equally acceptable interpretations: the one is physical, the other is mathematical. The former is a wave function as the exhausted description of a certain state of a certain quantum system. The latter chooses a certain mathematical structure among a certain category. Thus there is no way to be distinguished a mathematical structure from a physical state for both are described exhaustedly as a value of quantum information. This statement in turn can be utilized to be defined quantum information by the identity of any mathematical structure to a physical state, and also vice versa. Further, that definition is equivalent to both standard definition as the normed superposition and in-variance of Hamilton and Lagrange interpretation of mechanical motion introduced in the beginning of the paper. Then, the concept of information symmetry can be involved as the symmetry between three elements or two pairs of elements: Lagrange representation and each counterpart of the pair of Hamilton representation. The sense and meaning of information symmetry may be visualized by a single (quantum) bit and its interpretation as both (privileged) reference frame and the symmetries of the Standard model. (shrink)

It is not always obvious for even well-trained researchers to appreciate their peer’s scientific pursuits. In many cases, research results obtained from strenuous work processes could even be regarded as “useless knowledge”. -/- Only in very few places on this planet had the notion of useless knowledge been respected and sought after. That’s the famous IAS of Princeton University powered by the conception of the usefulness of useless knowledge of Abraham Flexner. That’s why brilliant scientists such as Albert Einstein, Kurt (...) Godel, and John von Neumann were among its first recruited members. -/- Our team has for many years now gone through various research problems. Still, it is difficult for even experienced and highly accomplished researchers to identify the type of IAS “useless knowledge” problems. But we never stopped trying. -/- Our latest try has led to the informational entropy-based definition of value. At first, it sounded weird for one to ponder the long-existing notion of value, which is used on a daily basis by everybody on Earth. In short, kind of... useless. But gradually, we have come to an understanding that the very familiarity of the word “value” has long obscured our question of its nature. -/- So, a bit about this newly minted definition is here for your perusal. (shrink)

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect (...) because truth-values do not supervene on semantic information, and misinformation is not a tyoe of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information. (shrink)

Information, and information and communication technologies (ICTs) are critical for most developed post-industrial societies. It follows, therefore, that the better the quality of the information exchanged, the more likely such societies and their members may prosper. But what is information quality (IQ) exactly? This paper discusses current definitions, problems and approaches to IQ and the question of how we should, and could, evaluate IQ in the future.

Estonian doesn't have a definite article. Instead, bare singular noun phrases can unambiguously bear either a definite interpretation or an indefinite interpretation. This paper argues that the pragmatic principles governing the felicitous use of three English articles ("a", "the" and "another"), described by A Grønn and KJ Sæbø (2012, 'A, the, another: A game of same and different' Journal of Logic, Language and Information 21, 75-95) can also account for the conditions under which a bare singular noun phrase in (...) Estonian bears a definite or instead an indefinite interpretation. The two languages use the same pragmatic principles to determine the definiteness interpretation of a noun phrase. The difference is just that in English (where definiteness meanings have been lexicalized) these pragmatic principles govern the felicity of article use, whereas in Estonian they govern the interpretation of a bare singular noun phrase. (shrink)

Ontologies are being used increasingly to promote the reusability of scientific information by allowing heterogeneous data to be integrated under a common, normalized representation. Definitions play a central role in the use of ontologies both by humans and by computers. Textual definitions allow ontologists and data curators to understand the intended meaning of ontology terms and to use these terms in a consistent fashion across contexts. Logical definitions allow machines to check the integrity of ontologies and reason over data (...) annotated with ontology terms to make inferences that promote knowledge discovery. Therefore, it is important not only to include in ontologies multiple types of definitions in both formal and in natural languages, but also to ensure that these definitions meet good quality standards so they are useful. While tools such as Protégé can assist in creating well-formed logical definitions, producing good definitions in a natural language is still to a large extent a matter of human ingenuity supported at best by just a small number of general principles. For lack of more precise guidelines, definition authors are often left to their own personal devices. This paper aims to fill this gap by providing the ontology community with a set of principles and conventions to assist in definition writing, editing, and validation, by drawing on existing definition writing principles and guidelines in lexicography, terminology, and logic. (shrink)

In this work, we propose a definition of logical consequence based on the relation between the quantity of information present in a particular set of formulae and a particular formula. As a starting point, we use Shannon‟s quantitative notion of information, founded on the concepts of logarithmic function and probability value. We first consider some of the basic elements of an axiomatic probability theory, and then construct a probabilistic semantics for languages of classical propositional logic. We define (...) the quantity of information for the formulae of these languages and introduce the concept of informational logical consequence, identifying some important results, among them: certain arguments that have traditionally been considered valid, such as modus ponens, are not valid from the informational perspective; the logic underlying informational logical consequence is not classical, and is at the least paraconsistent sensu lato; informational logical consequence is not a Tarskian logical consequence. (shrink)

Definition has the following features in Aristotle’s philosophy: 1. Each thing has only one definition and ‘it is impossible that there should be more than one definition for the same thing.’ (To., Z, 5, 142b^25; cf. To., Z, 4, 141a26) 2. Definition is ‘a formula of the essence’ (Met., H, 1042a17-18) and, thus, signifies the essence of the thing. (To., I, 5, ^101b30-) About the relation between definition and essence Aristotle regards three possibilities (PsA., B, (...) 94a11-14): a) A definition as an indemonstrable statement of essential nature. b) A definition as a syllogism of essential nature differing from demonstration in grammatical form. c) A definition as the conclusion of a demonstration giving essential nature. 3. ‘The definition is a formula and a formula has parts.’ (Met., H, 1042a18-20) Therefore, only the composite substances are definable and the primary parts of a composite substance are not definable. The reason is that ‘a definitory formula predicates something of something and one part of the definition must play the part of matter and the other that of form.’ (Met., H, 1043b28-32) Thus, definition is a sort of number: a divisible including indivisible parts. (Met., H, 1043b32-36) 4. To define a thing, one should give the species or the genera of the thing which are the only other things that can be substances of it and not its accidents. (Cat., 5, 2b31-36) Aristotle also brings differentiae into the definition: ‘There is nothing in the definition except the first-named genus and the differentiae. The other genera are the first genus and along with this the differentiae that are taken with, e.g. the first may be animal, the next animal which is footed, and again animal which is two-footed and featherless and …’ (Met., Z, 1037b28-33) Among genera the nearer genera are more informative because they are more distinctive and less general. (Cat., 5, 2b10-13 and b32-34) However, to give the species is always more informative and apt than giving the genus. (Cat., 5, 2b8-10) 5. Primary substances admit the definition of the species they are their individuals and of their genera. In the same way, species admit the definition of the genus. The reason is that everything said of the predicate can be said of the subject. (Cat., 5, 3b2-6) Therefore, everything admits the definition of its higher classes. 6. ‘Both the species and the individuals admit the definition of the differentia.’ (Cat., 5, 3b6-7) 7. A formula exhibiting the cause of a thing’s existence is a definition. (PsA., B, 10, 93b38-94a1) 8. It is possible to achieve the definition by division only if we keep three conditions in view (PsA., B, 97a23-26): a) The admission only of elements in the definable form. b) The arrangement of these elements in the right order c) The omission of no element in the definable form The process of division (PsA., B, 97a37-b6) is the process of dividing the genus by its differentia to the right species, the one that the subject accepts as its predicate, and again dividing the whole such searched by its right differentia to a predicable species. This process will be continued until we reach to that which is not further divisible, ‘i.e. that as soon as we have taken the last differentia to form the concrete totality, this totality admits of no division into species.’ In this way we achieve to a series of elements all in the definable forms without superfluous addition and without omission of any necessary element. This series includes the primary genus with all the differentia until it achieves to that which would admit of no division. The second condition, the right order, is the order in which that which is posited as primary be the one that is predicable of all of the other and not vice versa. The order must, then, be from more predicables to less predicables: ‘The right order will be achieved if the right term is assumed as primary, and this will be ensured if the term selected is predicable of all the other but not all they of it; since there must be one such term. Having assumed this, we at once proceed in the same way with the lower terms; for our second term will be the first of the remainder, our third the first of those which follow the second in a ‘contiguous’ series, since when the higher term is excluded, the term of the remainder which is ‘contiguous’ to it will be primary, and so on.’ (PsA., B, 97a26-34) 9. Things that are not the same must have different definitions. However, this does not mean that things that are the same must necessarily have the same definition. (To., I, 5, ^102a17-) 10. ‘Everything applicable to property and genus and accident will be applicable to definition as well.’ (To., I, 6, 102b27-) 11. ‘A name, e.g. ‘round’, means vaguely a sort of whole: its definition analyses this into its particular senses.’ Definition must be done through terms that are prior and more familiar and ‘anyone who has not defined a thing through terms that are prior and more familiar has not defined it at all.’ (To., Z, 4, 141a26-) It is indeed this very point that is the basis of definition by genus and differentiae: ‘A correct definition must define a thing through its genus and its differentiae, and these belong to the order of things which are without qualification more familiar than, and prior to, the species.’ (To., Z, 4, 141b^15-) This more familiarity, however, must be without qualification, i.e. not more familiar to certain people or in certain times. Otherwise, definition could not come always to be one and the same. (To., Z, 4, ^142a1-) . 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The notions of information, representation and enaction entertain historical and complex relations with cognition. Historical relations because representational structures belong to the central hypothesis of cognitive sciences. Complex relations because cognitive sciences apply the notion of representation to animals, humans and robots, and also because the enactive approach tends to disregard the GOFAI type of representations. In this wide horizon of relations, we propose to look at a systemic approach that could bring up a common denominator for information (...) and representations in the build up of cognition, and also keep a link with the enactive approach. Our purpose is to show that systems submitted to constraints can generate meaningful information to maintain their natures, and consequently build up meaningful representations that have some compatibility with the enactive approach. Such a systemic approach to the notion of meaningful information could then make available a link between enaction and meaningful representations. The first part of the presentation is about reminding that cognition does not exist per se, but is related to the system that builds it. We look at cognition as constituted by dynamic meaningful representations built up by systems that have constraints to satisfy in their environments. Cognition is considered here at the level of the system that builds it and uses it in order to maintain its nature in its environment. Such a systemic approach fits with evolution. Organisms build representations to cope with survival constraints (frogs build representations of moving black dots in order to satisfy food constraints). Humans build representations and cognition to satisfy constraints that are conscious and unconscious. Artificial systems can use representations and cognition to run activities related to constraints implemented by the designers or coming from the environment (a goal to reach being considered as a constraint to satisfy). In the second part of the presentation we define what are a meaningful information and a representation for a system submitted to a constraint in its environment, and we link these to the enactive approach. We define a meaningful information (a meaning) as an information generated by a system submitted to a constraint when it receives an external information that has a connection with the constraint. The meaning is precisely that connection. The meaning belongs to the interactions that link the system to its environment. The function of the meaning is to participate to the determination of an action that will be implemented in order to satisfy the constraint. (Menant, 2003). The satisfaction of the constraint goes with maintaining the nature of the system in its environment. A Meaning Generator System (MGS) is defined correspondingly. It is a building block for higher level systems. We present some characteristics of the MGS (groundings of a meaning, domain of efficiency and transfer of meanings, networking of meanings, evolutionary usage). The MGS approach is close to a simplified version of the Peircean triadic theory of signs (Menant, 2003, 2005 ). We define the representation of an item for a system as being the dynamic set of meaningful information corresponding to the item for the system in its environments (an elementary representation being made of a single meaningful information). These representations link the system to its environment by their meaningful components related to the nature of the system. These representations are different from the GOFAI ones. The possibilities for linking these notions of meaning and representation with the enactive approach come from the structure of the MGS: the need for an action is the cause of the meaning generation by and for the system. The action on the environment is for the system to maintain its nature (its identity). The MGS links together the generation of meaningful representations, the nature of the system, and the interactions with the environment. This can be considered as close to enacting a world by meaning generation (Di Paolo and all 2007), and to the enactive concept of sense making (De Jaegher, Di Paolo 2007). We propose that basing the definition of a representation on the notion of meaningful information generated by a system submitted to a constraint can open a way for making the notion of representation compatible with the enactive approach. In the third part of the presentation, we consider some cases of meaningful information and representations for organisms and for robots. Regarding organisms, the MGS can be used in an evolutionary context by looking at the evolution of the systems and of the constraints. Purpose is to modelize the generation of meanings and of representations in order to make available a tool usable for different levels of evolution, as evolution has a place in cognitive sciences (Proust, 2007). Constraints for basic life are survival constraints (individual and species). Group life constraints are also to be considered. Reaching the level of humans in evolution brings in new constraints that cannot be clearly identified as they have to take into account human consciousness which is today a mystery (the “hard problem”). On an evolutionary standpoint, human constraints come in addition to the ones existing for non human organisms. We can make some hypothesis on the nature of human constraints (Maslow pyramid based constraints, anxiety limitation…). For robots, the MGS is initially based on the design of the robot. The meaning generated within a robot is initially derived from the constraints implemented by the designer and from the environment. But some non calculable or non predictable evolutions of the robot can introduce meanings that look proper to the robot. This last point can be linked to the notion of autonomy in robots. In such examples, the dynamic management of meanings thru the MGSs in their environments keeps the link with the enactive approach. We finish the presentation by summarising the points addressed and by proposing several continuations. (shrink)

About six weeks ago, our post referred to the long-winding path to a new theoretical innovation as the pursuit of “useless knowledge” in Flexner’s terms. That little creation is the freshly minted informational entropy-based definition of value, presented in a very short paper, initially regarded by its authors as a research note. (And it still is.) Well, only two and a half months since its birth, this new concept of value has had enough time to power up several of (...) our publications in different disciplinary fields. The first published paper using the new definition deals with climate change denialism. The second paper (forthcoming) discusses the problem of academic retractions amidst the growing influence of generative AI. And the third, just accepted, explains the underlying mechanism of submission mechanism employed by journal editors and peer-reviewers, and the information-value nexus associated with it. (shrink)

How much value can our decisions create? We argue that unless our current understanding of physics is wrong in fairly fundamental ways, there exists an upper limit of value relevant to our decisions. First, due to the speed of light and the definition and conception of economic growth, the limit to economic growth is a restrictive one. Additionally, a related far larger but still finite limit exists for value in a much broader sense due to the physics of (...) class='Hi'>information and the ability of physical beings to place value on outcomes. We discuss how this argument can handle lexicographic preferences, probabilities, and the implications for infinite ethics and ethical uncertainty. (shrink)

The purpose of this paper is to inquire into the relationship between persuasive definition and common knowledge (propositions generally accepted and not subject to dispute in a discussion). We interpret the gap between common knowledge and persuasive definition (PD) in terms of potential disagreements: PDs are conceived as implicit arguments to win a potential conflict. Persuasive definitions are analyzed as arguments instantiating two argumentation schemes, argument from classification and argument from values, and presupposing a potential disagreement. The argumentative (...) structure of PDs reveals different levels of disagreement, and different pos-sibilities of resolving the conflict or causing dialogical deadlock. (shrink)