التفاصيل البيبلوغرافية
| العنوان: |
Concept Creation with Regulated Activation Networks |
| المؤلفون: |
Sharma, Rahul |
| المساهمون: |
Ribeiro, Bernardete Martins, Cardoso, Fernando Amílcar Bandeira |
| سنة النشر: |
2020 |
| المجموعة: |
Universidade de Coimbra: Estudo Geral |
| مصطلحات موضوعية: |
Computational Modeling, Dynamic Modeling, Machine Learning, Abstract Concept Modeling, Concept Learning, Concept Reconstruction, Modelação Computacional, Modelação Dinâmica, Aprendizado de máquina, Modelação de Conceito Abstrato, Aprendizagem de Conceito, Reconstrução de conceito, Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
| الوصف: |
Doctoral thesis submitted to the Doctoral Program in Information Science and Technology, presented to the Faculty of Sciences and Technology of the University of Coimbra ; Concepts are of great value to humans because they are one of the building blocks of our cognitive processes. They are involved in cognitive functions that are fundamental in decision making such as classification and also capacitate us for contextual comprehension. By definition, a concept refers to an idea or a combination of several ideas. In a computational context, a concept can be a feature or a set of features. An individual concept is referred to as a concrete concept, whereas a generalized form of a set of concepts can be perceived as an abstract concept. Computational concepts can be characterized in three broad categories; i.e. symbolic (e.g. Adaptive Control of Thought based approach), distributed (e.g. Neural Networks) and spatial (e.g. Conceptual Space) representations. CLARION, a cognitive architecture, is an example of a hybrid computational framework that combines symbolic and distributed representations. Moreover, the symbolic, distributed, spatial and hybrid representations are mostly used on representing concrete concepts, whereas the notion of an abstract concept is rarely explored. In this thesis, we propose a computational cognitive model, named Regulated Activation Network (RAN), capable of dynamically forming the abstract representations of concepts and to unify the qualities of spatial, symbolic and distributed computational approaches. Our model aims to simulate the cognitive processes of concept learning, creation and recall. In particular, the RAN’s modeling has three learning mechanisms where two perform inter-layer learning that helps in propagating activations from an input-to-output layer and vice versa. The third provides an intra-layer learning that is used to emulate regulation mechanism, which is inspired by biological Axoaxonic synapse where one node in a layer induces excitatory, neutral or inhibitory ... |
| نوع الوثيقة: |
doctoral or postdoctoral thesis |
| اللغة: |
English |
| Relation: |
PTDC/EEI-SCR/2072/2014; info:eu-repo/grantAgreement/EC/FP7/611733/EU/Concept Creation Technology; http://hdl.handle.net/10316/94990; 101569750 |
| الاتاحة: |
http://hdl.handle.net/10316/94990 |
| Rights: |
info:eu-repo/semantics/openAccess |
| رقم الانضمام: |
edsbas.C41EA012 |
| قاعدة البيانات: |
BASE |