The relations between ontology and information are many and fundamental, and they help us to understand the present gulf between (formal) ontology and (philosophical) Ontology: We can speak of respectively ontology-driven information and information-driven ontology as the focus on being informed vs. informed being. The question of whether these two (can) coincide is relevant to both fields, and in this article I elaborate on what needs to be addressed first of all to provide us with an answer: The form. This (...) core ontological concept rooting in Aristotelian metaphysics was central to philosophical ontology, in particular in Latin Scholasticism, when it was clearly put into relation with information as that which defines an entity. In this context, Dietrich of Freiberg synthesized this long debate in a way that matters not only to the philosophical effort of producing information-driven ontologies but also to the engineering constructs of ontology-driven information systems. (shrink)

Genera, typically hand-in-hand with their branching species, are essential elements of vocabulary-based information constructs, in particular scientific taxonomies. Should they also feature in formal ontologies, the highest of such constructs? I argue in this article that the answer is “Yes” and that the question posed in its title also has a Yes-answer: The way medieval ontologists sliced up the world into genera does matter to formal ontology. More specifically, the way Dietrich of Freiberg, a Latin scholastic, conceived and applied strictly (...) generic criteria to slice up the world into its entities can provide some guidelines to the field of formal ontology with respect to not only its contents, but also its scope. In particular, Dietrich's information criterion plays here a central role. (shrink)

A. Newell and H. A. Simon were two of the most influential scientists in the emerging field of artificial intelligence (AI) in the late 1950s through to the early 1990s. This paper reviews their crucial contribution to this field, namely to symbolic AI. This contribution was constituted mostly by their quest for the implementation of general intelligence and (commonsense) knowledge in artificial thinking or reasoning artifacts, a project they shared with many other scientists but that in their case was theoretically (...) based on the idiosyncratic notions of symbol systems and the representational abilities they give rise to, in particular with respect to knowledge. While focusing on the period 1956-1982, this review cites both earlier and later literature and it attempts to make visible their potential relevance to today's greatest unifying AI challenge, to wit, the design of wholly autonomous artificial agents (a.k.a. robots) that are not only rational and ethical, but also self-conscious. (shrink)

For millennia, knowledge has eluded a precise definition. The industrialization of knowledge (IoK) and the associated proliferation of the so-called knowledge communities in the last few decades caused this state of affairs to deteriorate, namely by creating a trio composed of data, knowledge, and information (DIK) that is not unlike the aporia of the trinity in philosophy. This calls for a general theory of knowledge (ToK) that can work as a foundation for a science of knowledge (SoK) and additionally distinguishes (...) knowledge from both data and information. In this paper, I attempt to sketch this generality via the establishing of both knowledge structures and knowledge systems that can then be adopted/adapted by the diverse communities for the respective knowledge technologies and practices. This is achieved by means of a formal–indeed, mathematical–approach to epistemological matters a.k.a. formal epistemology. The corresponding application focus is on knowledge systems implementable as computer programs. (shrink)

Contemporary studies in unconscious cognition are essentially founded on dissociation, i.e., on how it dissociates with respect to conscious mental processes and representations. This is claimed to be in so many and diverse ways that one is often lost in dissociation. In order to reduce this state of confusion we here carry out two major tasks: based on the central distinction between cognitive processes and representations, we identify and isolate the main dissociation paradigms; we then critically analyze their key tenets (...) and reported findings. (shrink)

Since Freud and his co-author Breuer spoke of dissociation in 1895, a scientific paradigm was painstakingly established in the field of unconscious cognition. This is the dissociation paradigm. However, recent critical analysis of the many and various reported dissociations reveals their blurred, or unveridical, character. Moreover, we remain ignorant with respect to the ways cognitive phenomena transition from consciousness to an unconscious mode. This hinders us from filling in the puzzle of the unified mind. We conclude that we have reached (...) a Kuhnian crisis in the field of unconscious cognition, and we predict that new models, incorporating partly the relevant findings of the dissociation paradigm—but also of dynamic psychology—, will soon be established. We further predict that some of these models will be largely based on the pairs representation–process and analog–digital. (shrink)

The traditional model of human cognition (TMHC) postulates an ontological and/or structural gap between conscious and unconscious mental representations. By and large, it sees higher-level mental processes as commonly conceptual or symbolic in nature and therefore conscious, whereas unconscious, lower-level representations are conceived as non-conceptual or sub-symbolic. However, experimental evidence belies this model, suggesting that higher-level mental processes can be, and often are, carried out in a wholly unconscious way and/or without conceptual representations, and that these can be processed unconsciously. (...) This entails that the TMHC, as well as the theories on mental representation it motivates and that in turn support it, is wrong. (shrink)