Farshad Badie

Formal thought disorder (FTD) is a clinical mental condition that is typically diagnosable by the speech productions of patients. However, this has been a vexing condition for the clinical community, as it is not at all easy to determine what “formal” means in the plethora of symptoms exhibited. We present a logic-based model for the syntax–semantics interface in semantic networking that can not only explain, but also diagnose, FTD. Our model is based on description logic (DL), which is well known for its adequacy to model terminological knowledge. More specifically, we show how faulty logical form as defined in DL-based Conception Language (CL) impacts the semantic content of linguistic productions that are characteristic of FTD. We accordingly call this the dyssyntax model.

Logical analysis of the applicability of nominals (which are introduced by hybrid logic) in the formal descriptions of the world (within modern knowledge representation and semantics-based systems) is very important because nominals, as second sorts of propositional symbols, can support logical identification of the described world at specific [temporal and/or spacial] states. This paper will focus on answering the philosophical-logical question of ‘how a fundamental world description in description logic (DL) and a nominal can be related to each other?’. Based on my assumption that nominals can support more adequate identification of the world in DL, this paper will deal with the concept of ‘world identification’. Accordingly, based on a logical-terminological analysis of nominals, the paper will analyse hybridised fundamental world descriptions. The research will finally reach the idea that we can have a hybrid description logic based on the analysed concepts.

This research works within the framework of constructivist learning (based on constructivist epistemology) and examines learning as an activity of construction, and it posits that knowledge acquisition (and learning) are transformative through self-involvement in some subject matter. Thus it leads, through this constructivism to a pedagogical theory of learning. I will mainly focus on conceptual and epistemological analysis of humans’ conceptualisations based on their own mental objects (schemata). Subsequently, I will propose an analytical specification of humans’ conceptualisations and understandings over their mental structures in the framework of constructivism, and I will clarify my logical [and semantic] conceptions of humans’ concept understandings. This research focuses on the philosophy of education and on logics of human learning. It connects with the topics ‘Cognition in Education’ and ‘Mental Models’.

Description Logics (DLs) are a family of formal knowledge representation formalisms and the most well-known formalisms in semantics-based systems. The central focus of this research is on logical-terminological characterisation/analysis of possibilistic and probabilistic descriptions of events in DLs. Based on a logical characterisation of the concept of `being', this paper conceptualises events within DLs world descriptions. Accordingly, it deals with the concepts of `possibility of events' and `probability of events'. The main goal of this research is to investigate how possible and probable notations can, terminologically and logically, be interpreted and analysed within DLs world descriptions. In other words, the research logically-terminologically investigates how possibilistic and probabilistic descriptions of events can be expressed in DLs.

Cognitive, or knowledge, agents, who are in some way aware of describing their own view of the world (based on their mental concepts), need to become concerned with the expressions of their own conceptions. My main supposition is that agents’ conceptions are mainly expressed in the form of linguistic expressions that are spoken, written, and represented based on e.g. letters, numbers, or symbols. This research especially focuses on symbolic conceptions (that are agents’ conceptions that are manifested in the form of their symbols). I attempt to logically (and using ????LSYM) analyse symbolic conceptions in terminological systems. ????LSYM is an assertional fragment of my developed Conception Language (????L), which is utilised as a formal-logical system for representing and explicating agents’ conceptions of the world. Keywords: assertional logic; cognitive agent; knowledge agent; conception language; conception; symbol; symbolic conception.

This original research hypothesises that the most fundamental building blocks of logical descriptions of cognitive, or knowledge, agents’ descriptions are expressible based on their conceptions (of the world). This article conceptually and logically analyses agents’ conceptions in order to offer a constructivist- based logical model for terminological knowledge. The most significant characteristic of [terminological] knowing is that there are strong interrelationships between terminological knowledge and the individualistic constructed, and to-be-constructed, models of knowledge. Correspondingly, I conceptually and logically analyse conception expressions based on terminological knowledge, and I show how terminological knowledge may reasonably be assumed to be constructed based on the agents’ conceptions of the world. The focus of my model is on terminological knowledge structures, which may find applications in such diverse fields as the Semantic Web and educational/learning systems.

The opinion defended in this paper is that the interrelationships between the phenomena of data and information can provide a strong basis for analyzing knowledge as a quantified and qualified construction. As other models (e.g., Augusto’s General Theory of Knowledge) suggest, it is important to distinguish knowledge from both data and information in the complicated trio composed of data, information, and knowledge (DIK). However, data and information can be combined into informative data. Taking into account quantified and qualified informative data, I speak here of quantified and qualified knowledge structures.

This article attempts to make a conceptual and epistemological junction between human learning and machine learning. I will be concerned with specifying and analysing the structure of concepts in the common ground between a concept-based human learning theory and a concept-based machine learning paradigm. I will focus on (i) humans’ conceptual representations in the framework of constructivism (as an educational theory of learning and model of knowing) and constructionism (as a theory for conceptualising learning) and (ii) concept representations in the framework of inductive concept learning (as an inductive machine learning paradigm). The results will support figuring out the most significant key points for constructing a conceptual linkage between a human learning theory and a machine learning paradigm. Accordingly, I will construct a conceptual ground for expressing and analysing concepts in the common ground of human and informatics sciences and in the context of human-machine interplays.

Regarding constructivism as a learning philosophy and/or a model of knowing, a person (learner or mentor) based on her/ his preconceptions and on personal knowings could actively participate in an interaction with another person (learner or mentor) in order to construct her/his personal knowledge. In this research I will analyse 'meaning construction' within constructivism. I will focus on a semantic loop that the learner and mentor as intentional participants move through and organise their personal constructed conceptions in order to construct meanings and produce their individual meaningful comprehensions. Subsequently, I will provide a semantic framework for analysing the meaning construction based on personal knowings and personal conceptions within constructivist interactions. This research could propose a new scheme for interpretation based on semantics and on interaction.

Arthur Norman Prior was born on 4 December 1914 in Masterton, New Zealand. He studied philosophy in the 1930s and was a significant, and often provocative, voice in theological debates until well into the 1950s. He became a lecturer in philosophy at Canterbury University College in Christchurch in 1946 succeeding Karl Popper. He became a full professor in 1952. He left New Zealand permanently for England in 1959, first taking a chair in philosophy at Manchester University, and then becoming a fellow of Balliol College, Oxford, in 1966. Prior died on 6 October 1969 in Trondheim, Norway. After Prior’s death, many logicians and philosophers have analysed and discussed his approach to formal and philosophical logic. In particular, his contributions to modal logic, tense-logic and deontic logic have been studied. In 1957, A.N. Prior proposed the three-valued modal logic Q as a ‘correct’ modal logic from his philosophical motivations, see Prior (1957). Prior developed Q in order to offer a logic for contingent beings, in which one could intelligibly and rationally state that some beings are contingent and some are necessary, see Akama & Nagata (2005). According to Akama & Nagata (2005), Q has a natural semantics. In other words, from the philosophical point of view, Q can be regarded as an ‘actualist’ modal logic. This review article is a developed description of, and discussion on, ‘The System Q’ that is the fifth chapter of Prior (1957). In addition, in his logical analysis of ‘Time & Existence’ (that is the eights chapter of Prior (1967)), Prior has worked on system Q. Thus, Prior (1967) has also been very useful for this article. This article analyses the logical structure of system Q in order to provide a more understandable description as well as logical analysis for today’s logicians, philosophers, and information-computer scientists. In the paper, the Polish notations are translated into modern notations in order to be more comprehensible and to support the developed formal descriptions as well as semantic analysis.

Description Logics (DLs) are a family of well-known terminological knowledge representation formalisms in modern semantics-based systems. This research focuses on analysing how our developed Occurrence Logic (OccL) can conceptually and logically support the development of a description logic. OccL is integrated into the alternative theory of natural language syntax in `Deviational Syntactic Structures' under the label `EFA(X)3' (or the third version of Epi-Formal Analysis in Syntax, EFA(X), which is a radical linguistic theory). From the logical point of view, OccL is a formal logic that mainly deals with the occurrences of symbols as well as with their priorities within linguistic descriptions, i.e. natural language syntax, semantics and phonology. In this article---based on our OccL-based definitions of the concepts of `strong implication' and `occurrence value' as well as of the logical concept `identical occurrence constructor (IDOC)' that is the most fundamental logical concept in our formalism---we will model Occurrence Description Logic ($\mathcal{ODL}$). Accordingly, we will formally-logically analyse `occurrence(s) of symbol(s)' within descriptions of the world in $\mathcal{ODL}$. In addition, we will analyse and assess the logical concepts of `occurrence' and `occurrence priority' in $\mathcal{ODL}$. This research can make a strong logical background for our future research in the development of a Modal Occurrence Description Logic.

The opinion defended in this paper is that the interrelationships between the phenomena of data and information can provide a strong basis for analyzing knowledge as a quantified and qualified construction. As other models (e.g., Augusto’s General Theory of Knowledge) suggest, it is important to distinguish knowledge from both data and information in the complicated trio composed of data, information, and knowledge (DIK). However, data and information can be combined into informative data. Taking into account quantified and qualified informative data, I speak here of quantified and qualified knowledge structures.

In this research, Description Logics (DLs) will be employed for logical description, logical characterisation, logical modelling and ontological description of concept understanding in terminological systems. It’s strongly believed that using a formal descriptive logic could support us in revealing logical assumptions whose discovery may lead us to a better understanding of ‘concept understanding’. The Structure of Observed Learning Outcomes (SOLO) model as an appropriate model of increasing complexity of humans’ understanding has supported the formal analysis.

I have supposed that we need a formal system to represent and explain humans' conceptions of the world. According to this research, such a formal system is representable based on a Conception Language (CL) that is a terminological knowledge representation formalism. In this research, I will offer a formal ontology for conception representation in terminological systems. Such a CL-based ontology will specify the conceptualization of humans' conceptions as well as of the effects of their conceptions on the world.

This research provides a contextual description concerning an existential and structural analysis of ‘Relations’ between human beings and machines. Subsequently, it will focus on the conceptual and epistemological analysis of (i) my own semantics-based framework [for human meaning construction] and of (ii) a well-structured machine concept learning framework. Accordingly, I will, semantically and epistemologically, focus on linking those two frameworks for logical analysis of concept learning in the context of human-machine interrelationships. It will be demonstrated that the proposed framework provides a supportive structure over the described contextualisation of ‘relations’ between human beings and machines within concept learning processes.

Although formal thought disorder (FTD) has been for long a clinical label in the assessment of some psychiatric disorders, in particular of schizophrenia, it remains a source of controversy, mostly because it is hard to say what exactly the “formal” in FTD refers to. We see anomalous processing of terminological knowledge, a core construct of human knowledge in general, behind FTD symptoms and we approach this anomaly from a strictly formal perspective. More specifically, we present here a symbolic computational model of storage in, and activation of, a human semantic network, or semantic memory, whose core element is logical form; this is normalized by description logic (DL), namely by CL, a DL-based language – Conception Language – designed to formalize conceptualization from the viewpoint of individual cognitive agency. In this model, disruptions in the rule-based implementation of the logical form account for the apparently semantic anomalies symptomatic of FTD, which are detected by means of a CL-based algorithmic assessment.