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Abstract: Abduction, which is a kind of inference, is clearly articulated by C.S. Peirce (Peirce 1868; 1955). Although abduction is considered as reasoning with uncertainty (Finlay and Dix, 1996), it has been studied in artificial intelligence and computer science (Bylander et al 1991; Abe 2003). Recently, constructing a dynamical model which represents logical inferences, Sawa and Gunji use an arrow diagram which represents three types of inference articulated by Peirce (i.e. deduction, induction and abduction). This formalization for abduction is not only consistent with the preceding studies (Peirce 1868; Finlay and Dix 1996), but also opens up the way by which abduction can be applied to numerical function systems (Kamiura 2010). In this paper, based on the Sawa-Gunji's inference diagram, a numerical aspect of abduction is formalized as incomplete parameter estimation.

Abstract: This paper suggests those interested in a Science of Information establish an entirely new academic and scientific discipline to be titled "Science of Information". This new discipline should be established as a meta-discipline because the new discipline will include the theoretical work of and complement the other disciplines. It should exist equally with traditional disciplines such as physical, social science, arts, and humanities. It should not compete with or replace other disciplines. It should stand alongside them and assist them, as well as conduct comparisons and consolidations amongst the disciplines regarding information theories, methodologies, practices, by adding new perspectives, resources and developments.

Abstract: Based upon the natural limits of observation, we tackle a critical review of Dretske's approach to information, knowledge and perception. The physics of the manifestation of an arbitrary object –tackled in Part 2 as a separate article– sets forth an informational boundary stating that information cannot be enough to support our cognitive processes. The problems do not rely –as Dretske supposes- on the lacks of the channel, but on the very nature of observation. Furthermore, Dretske's approach –handcuffed to his maximalist support on information- presents some lacks concerning processual character of information, fuzziness of perception and knowledge, contents de dicto and conventional regularities. The posed limits and problems intend to settle new foundations for a more refined conjunction of information and knowledge.

Abstract: In this second part of our inquiry into the relation between information and cognition, we delve into the physical limits of the manifestation of an arbitrary object first with independence of any observer, then considering the nature of perception. The analysis of the manifestations of an object in a homogeneous environment by means of wave phenomena shows that the information carried by such manifestations offers a constitutive fuzziness and ambiguity of the observed object. On the one hand, the details that can be specified concerning the object are strictly limited by the wave length; on the other hand, the volumetric details of the object (i.e. its bowls) are outlawed to the observer, not in virtue of the object opacity, but to the very dimension or complexity of the wave phenomenon in the space surrounding the object. The analysis of perception, considering this physical boundary and the specificity of the animal sensitivity, shows the combined role of other concurrent or previous percept and some a priori knowledge in the perception and awareness of reality.

Abstract: A common usage of the concept of information requires a unique definition of it. The text expands on a proposal for an ontology of information, which will be grounded in physics. Shannon's communication theory does not conceptualize any physical variable. It will be shown that by doing so the gap between syntax and semantics can be closed by introducing the universal category of triadic information. Any informational scenario is given by the trias of a) a sender, and of b) the transformation which happens to c) the receiver. The concept of information is taken in a broader sense, and is based on physical fundaments. The gravitational force which is exploited to a physical body holds in the same sense well defined information as a spontaneous appearance of a new, algorithmically underivable structure or event: the world gets 'completed' within a continuous informational process. Any spontaneous process will always happen in order to increase the entropy of the world. That is, such fundamental information which causes this completion process is given within our universe. For those reasons we have to state, that information causes any causal process, rather than 'is' a causal process. All living species are grounded on an information-receiving, heteronomous deep structure, which includes as well the message which corresponds to further autonomy and freedom (the completion theorem). To summarize, we are enabled to create and to enter into the so called information society by ontological evidence. Based on such foundations, an adequate concept for computer science will be shortly introduced.

Abstract: Many social researchers and economists observe changes in the structure of labor in contemporary society, pointing out information and knowledge as key elements of labor. Still analysis of that content is often hampered by the confusion of terms, and objectionable simplification. This article suggests some approaches to introduce clarity in the role of information and knowledge in the structure of labor.

Abstract: The essential methodology in social science to "understand" phenomena is informed abstraction. But the way - how and what for - the abstraction process is shaped divides the economists into various schools. While mainstream economists abstract from any links of the economy to human beings - replacing them by selfish machines maximizing their profits or individual utilities, and neglecting any deeper analysis of the basic constructions they use (like prices or money), heterodox economists try to look behind the surface, link them to certain periods of history and to the source of all value: humans are social beings and cannot exist without mutuality. The paper presents a heterodox way to reconstruct contemporary capitalist economies by applying the new science of information with its evolutionary concepts. It starts the description on a very abstract level: useful things and services produced by specialized labor. Step by step new layers of information are added. At the same time economic indicators of the lower levels are modified (labor values, competition leading to prices of production, money and banks, state activities, monopoly), ending at the surface of the economy with the introduction of commodification and commercialization processes of information in the so called information society. The result of the reconstruction is used in a mathematical simulation model based on stylized facts.

Abstract: Any living cell parasitizing a host organism is immersed into a molecular environment of unfathomable complexity. For the advancement of its life cycle in such "hostile" a territory, the cell has to carefully sense its environment, "see" the ongoing physiological processes taking place, and guide subsequently its own network of self-construction processes, pathological responses included. We will discuss how this informational matching occurs in the bacillus Mycobacterium tuberculosis, and how transcriptional programs within the global transcriptional regulatory network are deployed in response to specific signals from the environment and from within the cell itself. In the era of the bioinformatic revolution and of systems biology, it is perhaps surprising that the functional interconnection between the transcription network and the signaling system is far from clarified yet. In the extent to which the living cell can be considered as one of the central paradigms of the nascent information science, this discussion becomes one about the essential cluster of concepts which should potentially apply to the analysis of other information-based entities.