46 research outputs found
Function-Theoretic Explanation and the Search for Neural Mechanisms
A common kind of explanation in cognitive neuroscience might be called functiontheoretic:
with some target cognitive capacity in view, the theorist hypothesizes that
the system computes a well-defined function (in the mathematical sense) and explains
how computing this function constitutes (in the systemâs normal environment) the
exercise of the cognitive capacity. Recently, proponents of the so-called ânew mechanistâ
approach in philosophy of science have argued that a model of a cognitive capacity is
explanatory only to the extent that it reveals the causal structure of the mechanism
underlying the capacity. If they are right, then a cognitive model that resists a transparent
mapping to known neural mechanisms fails to be explanatory. I argue that a functiontheoretic
characterization of a cognitive capacity can be genuinely explanatory even
absent an account of how the capacity is realized in neural hardware
Semantics and the stratification of explanation in cognitive science
This work is concerned with a pervasive problem in Cognitive Science which
I have called the "stratificational" approach. I argue that the division into
"levels of explanation" that runs as a constant theme through much work
in Cognitive Science and in particular natural language semantics, is in direct conflict with neuroscientific evidence. I claim it is also in conflict with
a right understanding of the philosophical notion of "evidence". The neuroscientific work is linked with the philosophical problem to provide a critique of concrete cases of research within the natural language semantics
community. More recent neuroscientifically aware research is examined
and it is demonstrated that it suffers similar problems due to the same
deep running assumptions as those which effect traditional formalist theory. The contribution of this thesis is thought to be that of a demonstration
of the essential nature and indeed the ubiquity of the basic assumptions in
the field. Also, a new link is forged between the concerns of the formalists
and certain seemingly more abstract philosophical work. This link enables
us to see how much philosophical problems infect research into cognition
and language. It is argued that practical research in Cognitive Science simply cannot be seen to be independent of the philosophical basis of the entire
subject. The resulting picture of Cognitive Science and its place is outlined
and explored with special emphasis on what I have called the "Principle
of Semantic Indistinguishabliity" which says that the contribution of what
can be broadly termed "environment" is epitemologically opaque to our cognition. The importance of this principle is discussed.The purpose of this work is to draw out a fundamental thread of reasoning and methodology that underlies most traditional work, and some not
so traditional work, in Cognitive Science. It will be argued that this line
of reasoning is at odds with the implications of modern neuroscience and
cannot base a reasonable claim to "explain" human cognition. The picture
I shall identify is that which I shall call "stratified". This, in general, is
an attempt at explanation that divides into "levels of explanation", each
with its own concepts that are said to be essential to the explanation of
a phenomenon. There are specific and pragmatic manifestations of this, I
discuss these in Chapter 3 and 7 in particular. There are also more abstract expressions of the same tendency which I examine mainly in Chapter 6. One of the principle tasks is to demonstrate the links between the
assumptions of the more abstract formulations of this approach and th eir
pragmatic instantiations in work in Cognitive Science. This allows it to be
made clear that certain methodological problems are ubiquitous within the
field and are not simply a result of the particular pragmatics of a particular
research area.In Cognitive Science as a whole, it is generally appreciated today that
there are problems to do with integration of traditional formal systems and
the evolutionary and biological aspects of human cognition. One aim of
this work is exactly to give an argument, supported from work in the brain
sciences, that a certain methodology - particularly that enshrined within
formal systems in language semantics - is strongly denied its evidential
basis as a result of certain empirical considerations. It is also denied much
of its basis as a result of the incongruity between the original motivations
of logical formalism and the use to which this formalism is put today. The
conclusion of this is that Cognitive Science's role in certain areas is severely
limited and it crucially relies on an amount of empirical brain research in
places thought usually to be completely separate from the "low-level" evidence from neuroscience. Part of my thesis is that stratified systems and
particularly systems of formal logic within linguistics and semantics, cannot possibly be independent in the way imagined. There is also exploration
of a general point regarding the character of the relation between strata in
a stratified theory. There is, I shall argue, an irresolvable tension between
the desire to have separate strata which are both independent but related.
We shall see this both in concrete terms in the discussion of Fodor and in
the abstract in the discussion of McDowell.George Lakoffhas expressed agreement with this particular premise:
" ... linguistic results ... indicate that human reason uses
some of the same mechanisms involved in perception and ... human reason can be seen as growing out of perceptual and motor
mechanisms."1If this is correct, then I think that there are enormous implications for
Cognitive Science in its practise of semantics since the mechanisms of motor and perceptual systems impose radical constraints when applied in the
area of semantics.Given this, my aim is to demonstrate that certain seemingly theoryindependent areas of research in Cognitive Science such as linguistics and
natural language semantics are actually infected with damaging assumptions from certain misguided philosophical positions. The idea that we can
simply model things in Cognitive Science and wait for someone else to sort
out the theoretical structure into which all of the models will fit is not tenable. I shall demonstrate this in several concrete cases and couple this with
a critique from neuroscience which is crucially related to a more philosophical critique of fundamental assumptions. The structure of the work is as
follows. Firstly, I give an overview of foundational issues in Cognitive Science by discussing central works. Then, I introduce the main problems in
concrete form by way of an examination of certain approaches to inference
in formal semantics. Chapter 4 expands on this in an analysis of the notion of "compositionality" with reference to the "stratificational" approach
I find apparent in traditional work in Cognitive Science and the assumptions it disguises. Chapter 5 introduces the themes from neuroscience and
the relations they have to the philosophical critique in Chapter 6. In Chapter 7, I demonstrate that the assumptions I have identified are present
even in work motivated by a desire to leave behind the formalist program.
I explain why this is the case and the implications this has for a correct
view of "evidence" in Cognitive Science. At this point, I deal with pertinent
objections to my view stemming from the parts of the discipline I have mentioned. Chapter 8 condenses the problem and shows the fundamentals of
the whole problem in relief, suggesting what all of the preceding means for
Cognitive Science
Apperceptive patterning: Artefaction, extensional beliefs and cognitive scaffolding
In âPsychopower and Ordinary Madnessâ my ambition, as it relates to Bernard Stieglerâs recent literature, was twofold: 1) critiquing Stieglerâs work on exosomatization and artefactual posthumanismâor, more specifically, nonhumanismâto problematize approaches to media archaeology that rely upon technical exteriorization; 2) challenging how Stiegler engages with Giuseppe Longo and Francis Baillyâs conception of negative entropy. These efforts were directed by a prevalent techno-cultural qualifier: the rise of Synthetic Intelligence (including neural nets, deep learning, predictive processing and Bayesian models of cognition). This paper continues this project but first directs a critical analytic lens at the Derridean practice of the ontologization of grammatization from which Stiegler emerges while also distinguishing how metalanguages operate in relation to object-oriented environmental interaction by way of inferentialism. Stalking continental (Kapp, Simondon, Leroi-Gourhan, etc.) and analytic traditions (e.g., Carnap, Chalmers, Clark, Sutton, Novaes, etc.), we move from artefacts to AI and Predictive Processing so as to link theories related to technicity with philosophy of mind. Simultaneously drawing forth Robert Brandomâs conceptualization of the roles that commitments play in retrospectively reconstructing the social experiences that lead to our endorsement(s) of norms, we compliment this account with Reza Negarestaniâs deprivatized account of intelligence while analyzing the equipollent role between language and media (both digital and analog)
Whole Set of Volume 1 No 1 (2010) of COMPARATIVE PHILOSOPHY
Whole Set of Contents of Current Issue (for cross-reference reading and hard-copy preservation of the whole issue
A Language-centered Approach to support environmental modeling with Cellular Automata
Die Anwendung von Methodiken und Technologien aus dem Bereich der Softwaretechnik auf den Bereich der Umweltmodellierung ist eine gemeinhin akzeptierte Vorgehensweise. Im Rahmen der "modellgetriebenen Entwicklung"(MDE, model-driven engineering) werden Technologien entwickelt, die darauf abzielen, Softwaresysteme vorwiegend auf Basis von im Vergleich zu Programmquelltexten relativ abstrakten Modellen zu entwickeln. Ein wesentlicher Bestandteil von MDE sind Techniken zur effizienten Entwicklung von "domĂ€nenspezifischen Sprachen"( DSL, domain-specific language), die auf Sprachmetamodellen beruhen. Die vorliegende Arbeit zeigt, wie modellgetriebene Entwicklung, und insbesondere die metamodellbasierte Beschreibung von DSLs, darĂŒber hinaus Aspekte der Pragmatik unterstĂŒtzen kann, deren Relevanz im erkenntnistheoretischen und kognitiven Hintergrund wissenschaftlichen Forschens begrĂŒndet wird. Hierzu wird vor dem Hintergrund der Erkenntnisse des "modellbasierten Forschens"(model-based science und model-based reasoning) gezeigt, wie insbesondere durch Metamodelle beschriebene DSLs Möglichkeiten bieten, entsprechende pragmatische Aspekte besonders zu berĂŒcksichtigen, indem sie als Werkzeug zur Erkenntnisgewinnung aufgefasst werden. Dies ist v.a. im Kontext groĂer Unsicherheiten, wie sie fĂŒr weite Teile der Umweltmodellierung charakterisierend sind, von grundsĂ€tzlicher Bedeutung. Die Formulierung eines sprachzentrierten Ansatzes (LCA, language-centered approach) fĂŒr die WerkzeugunterstĂŒtzung konkretisiert die genannten Aspekte und bildet die Basis fĂŒr eine beispielhafte Implementierung eines Werkzeuges mit einer DSL fĂŒr die Beschreibung von ZellulĂ€ren Automaten (ZA) fĂŒr die Umweltmodellierung. AnwendungsfĂ€lle belegen die Verwendbarkeit von ECAL und der entsprechenden metamodellbasierten Werkzeugimplementierung.The application of methods and technologies of software engineering to environmental modeling and simulation (EMS) is common, since both areas share basic issues of software development and digital simulation. Recent developments within the context of "Model-driven Engineering" (MDE) aim at supporting the development of software systems at the base of relatively abstract models as opposed to programming language code. A basic ingredient of MDE is the development of methods that allow the efficient development of "domain-specific languages" (DSL), in particular at the base of language metamodels. This thesis shows how MDE and language metamodeling in particular, may support pragmatic aspects that reflect epistemic and cognitive aspects of scientific investigations. For this, DSLs and language metamodeling in particular are set into the context of "model-based science" and "model-based reasoning". It is shown that the specific properties of metamodel-based DSLs may be used to support those properties, in particular transparency, which are of particular relevance against the background of uncertainty, that is a characterizing property of EMS. The findings are the base for the formulation of an corresponding specific metamodel- based approach for the provision of modeling tools for EMS (Language-centered Approach, LCA), which has been implemented (modeling tool ECA-EMS), including a new DSL for CA modeling for EMS (ECAL). At the base of this implementation, the applicability of this approach is shown
Second Generation General System Theory: Perspectives in Philosophy and Approaches in Complex Systems
Following the classical work of Norbert Wiener, Ross Ashby, Ludwig von Bertalanffy and many others, the concept of System has been elaborated in different disciplinary fields, allowing interdisciplinary approaches in areas such as Physics, Biology, Chemistry, Cognitive Science, Economics, Engineering, Social Sciences, Mathematics, Medicine, Artificial Intelligence, and Philosophy. The new challenge of Complexity and Emergence has made the concept of System even more relevant to the study of problems with high contextuality. This Special Issue focuses on the nature of new problems arising from the study and modelling of complexity, their eventual common aspects, properties and approachesâalready partially considered by different disciplinesâas well as focusing on new, possibly unitary, theoretical frameworks. This Special Issue aims to introduce fresh impetus into systems research when the possible detection and correction of mistakes require the development of new knowledge. This book contains contributions presenting new approaches and results, problems and proposals. The context is an interdisciplinary framework dealing, in order, with electronic engineering problems; the problem of the observer; transdisciplinarity; problems of organised complexity; theoretical incompleteness; design of digital systems in a user-centred way; reaction networks as a framework for systems modelling; emergence of a stable system in reaction networks; emergence at the fundamental systems level; behavioural realization of memoryless functions
Enhancing FunGramKB: Further Verbs of Feeling in English
The present dissertation aims at analyzing some linguistic aspects related to the lexical, semantic and syntactic behaviour of a number of verbs of FEELING in English whose lexical, grammatical and idiosyncratic properties have been entered into the FunGramKB Editor in application of study of the theoretical assumptions propounded by the Lexical-Constructional Model.
Analysis and subsequent input of data have been assessed against the background of some of the 20th-century trends in linguistics which find their expression in the first decade of this century, and the role of semantics in a world in which increasing priority is given to probabilistic, machine-learned output in lexicographic work. From this stance, the generic features contained in the FunGramKB meaning postulates and thematic frames as outlined in the Lexical-Constructional Model bring hope for a more faithful rendering of the semantic relationships established within human expression, while making provisions for a semanticistâs contribution to refinement and storage of both thorough and extensive knowledge
A framework for the analysis and evaluation of enterprise models
Bibliography: leaves 264-288.The purpose of this study is the development and validation of a comprehensive framework for the analysis and evaluation of enterprise models. The study starts with an extensive literature review of modelling concepts and an overview of the various reference disciplines concerned with enterprise modelling. This overview is more extensive than usual in order to accommodate readers from different backgrounds. The proposed framework is based on the distinction between the syntactic, semantic and pragmatic model aspects and populated with evaluation criteria drawn from an extensive literature survey. In order to operationalize and empirically validate the framework, an exhaustive survey of enterprise models was conducted. From this survey, an XML database of more than twenty relatively large, publicly available enterprise models was constructed. A strong emphasis was placed on the interdisciplinary nature of this database and models were drawn from ontology research, linguistics, analysis patterns as well as the traditional fields of data modelling, data warehousing and enterprise systems. The resultant database forms the test bed for the detailed framework-based analysis and its public availability should constitute a useful contribution to the modelling research community. The bulk of the research is dedicated to implementing and validating specific analysis techniques to quantify the various model evaluation criteria of the framework. The aim for each of the analysis techniques is that it can, where possible, be automated and generalised to other modelling domains. The syntactic measures and analysis techniques originate largely from the disciplines of systems engineering, graph theory and computer science. Various metrics to measure model hierarchy, architecture and complexity are tested and discussed. It is found that many are not particularly useful or valid for enterprise models. Hence some new measures are proposed to assist with model visualization and an original "model signature" consisting of three key metrics is proposed.Perhaps the most significant contribution ofthe research lies in the development and validation of a significant number of semantic analysis techniques, drawing heavily on current developments in lexicography, linguistics and ontology research. Some novel and interesting techniques are proposed to measure, inter alia, domain coverage, model genericity, quality of documentation, perspicuity and model similarity. Especially model similarity is explored in depth by means of various similarity and clustering algorithms as well as ways to visualize the similarity between models. Finally, a number of pragmatic analyses techniques are applied to the models. These include face validity, degree of use, authority of model author, availability, cost, flexibility, adaptability, model currency, maturity and degree of support. This analysis relies mostly on the searching for and ranking of certain specific information details, often involving a degree of subjective interpretation, although more specific quantitative procedures are suggested for some of the criteria. To aid future researchers, a separate chapter lists some promising analysis techniques that were investigated but found to be problematic from methodological perspective. More interestingly, this chapter also presents a very strong conceptual case on how the proposed framework and the analysis techniques associated vrith its various criteria can be applied to many other information systems research areas. The case is presented on the grounds of the underlying isomorphism between the various research areas and illustrated by suggesting the application of the framework to evaluate web sites, algorithms, software applications, programming languages, system development methodologies and user interfaces
Semantic Models and Reasoning for Building System Operations: Focus on Knowledge-Based Control and Fault Detection for HVAC
According to the U.S. Energy Information Administration (EIA), the Building Sector consumes nearly half (47.6%) of all energy produced in the United States. Seventy-five percent (74.9%) of the electricity produced in the United States is used just to operate buildings. At the same time, decision making for building operations still heavily rely on human knowledge and practical experience and may be far from optimal.
In a step toward mitigating these deficiencies, this dissertation reports on a program of research to identify opportunities for using semantic models and reason- ing in building system operations. The work focuses on knowledge-based control and fault detection for heating, ventilation and air conditioning (HVAC) systems. Decision-making procedures for building system operations are complicated by the multiplicity of participating domains (e.g., architecture, equipment, sensors, occu- pants, weather, utilities) that need to be considered. The key opportunity of this approach is a means to utilize semantic models for knowledge representation, inte- gration of heterogeneous data sources, and executable processing of semantic graph models in response to external events. The results of this dissertation are con- densed into three case-study applications; (1) Semantic-assisted model predictive control (MPC) for detection of occupant thermal comfort, (2) Semantic-based util- ity description for MPC in a chiller plant operation, and (3) Knowledge-based fault detection and diagnostics for HVAC systems