A Cognitive Computational Knowledge Representation Theory

A Cognitive Computational Knowledge Representation Theory

Mehdi Najjar (University of Sherbrooke, Canada) and André Mayers (University of Sherbrooke, Canada)
Copyright: © 2009 |Pages: 18
DOI: 10.4018/978-1-60566-170-4.ch017
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Encouraging results of last years in the field of knowledge representation within virtual learning environments confirms that artificial intelligence research in this topic find it very beneficial to integrate the knowledge psychological research have accumulated on understanding the cognitive mechanism of human learning and all the positive results obtained in computational modelling theories. This chapter introduces a novel cognitive and computational knowledge representation approach inspired by cognitive theories which explain the human cognitive activity in terms of memory subsystems and their processes, and whose aim is to suggest formal computational models of knowledge that offer efficient and expressive representation structures for virtual learning. Practical studies both contribute to validate the novel approach and permit to draw general conclusions.
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Almost since the advent of the computer age, researchers have recognised the computer’s enormous potential as an educational aid, and although the idea of using software resources for teaching and learning purpose dates back more than three decades, having recourse to virtual learning environments (VLE) in teaching and training constitute an axis of interest which has not stopped growing. Indeed, this important technological concept is being more and more considered by an increasing number of universities and colleges. Various attempts (Wells & Travis, 1996; Rzepa & Tonge, 1998; Lintermann & Deussen, 1999; Heermann & Fuhrmann, 2000) to create strongly interactive VLE were made, generating a remarkable enthusiasm within the educational community. However, if one has the ambition to build such environments that provide specific teaching material and exploit technology-based features and which are equipped with tutorial strategies able to interact with learners that have various levels of intelligence and different capacities of knowledge acquisition—especially, to adapt contents to each student profile and its needs (Brusilovsky & Peylo, 2003) and to provide tailored aid to learners according to their cognitive states (de Rosis, 2001), then understanding the human learning processes and the manners of structuring and handling knowledge during those processes is a fundamental task.

Recent multidisciplinary researches on cognitive informatics (Wang, 2003; Wang et al., 2003; Wang & Wang, 2006; Wang & kinsner, 2006) that study internal information processing mechanisms and processes of the brain (and that investigate how human beings acquire, interpret and express knowledge by using the memory and the mind) lead to seriously consider the idea to adopt a memory-based approach which perceives the memory as the foundation for any kind of intelligence. Incontestably, representing the acquired/handled knowledge of students during learning constitutes a real challenge. One solution to the outcome issues expressed above could be offered thanks to the adoption of a cognitive, computational and memory-based knowledge representation approach that formalise the structuring of the domain knowledge which is handled and/or acquired by learners during training activities via VLE.

In this chapter, we introduce AURELLIO1, a cognitive and computational knowledge representation approach inspired by cognitive theories which explain the human cognitive activity in terms of memory subsystems and their processes, and whose aim is to suggest formal computational models of knowledge representation. The proposed models are innovative in many respects. These models (1) use parsimoniously cognitive structures suggested by psychology to dynamically encode the knowledge, (2) take into account an episodic knowledge—defined within a novel context—whose analysis serves for a better understanding of the learner behaviour (Najjar et al., 2006), and (3) treat explicitly the student’s goals for reasoning purpose. The rest of the article is organised as follows. First, we present the AURELLIO knowledge representation theoretical approach. Second, we describe an AURELLIO-based authoring tool whose purpose is to facilitate modelling the domain knowledge via a user-centered graphical interface which is ergonomic and easy to use by non-experts in informatics. The objective (through this section) is to point out in detail the various knowledge representation structures proposed by AURELLIO. Third, we report on two practical studies that try to validate AURELLIO-based models of knowledge representation in the scope of the expressivity and efficiency contexts. In the first study, the objective was to conceive an AURELLIO model that represents the domain knowledge of a technical and rigorous discipline—the usage of reduction rules of algebraic Boolean expressions. In the second study, the focus was on the cognitive aspects of the AURELLIO knowledge representation and reasoning in comparison with ACT-R (Anderson, 1993), a famous and widely acknowledged cognitive architecture. Here, the interest was on modelling interrupted activities and the interruptions’ consequence on the task achievement. Fourth, we underline some originalities of AURELLIO and we discuss relations between our approach and the ACT-R knowledge representation theory. In the last section, by way of conclusion, we mention our current work.

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Table of Contents
Yingxu Wang
Chapter 1
Yingxu Wang
Cognitive Informatics (CI) is a transdisciplinary enquiry of the internal information processing mechanisms and processes of the brain and natural... Sample PDF
The Theoretical Framework of Cognitive Informatics
Chapter 2
Withold Kinsner
This chapter provides a review of Shannon and other entropy measures in evaluating the quality of materials used in perception, cognition, and... Sample PDF
Is Entropy Suitable to Characterize Data and Signals for Cognitive Informatics?
Chapter 3
Ismael Rodríguez, Manuel Núñez, Fernando Rubio
Finite State Machines (FSM) are formalisms that have been used for decades to describe the behavior of systems. They can also provide an intelligent... Sample PDF
Cognitive Processes by using Finite State Machines
Chapter 4
Yingxu Wang
An interactive motivation-attitude theory is developed based on the Layered Reference Model of the Brain (LRMB) and the Object-Attribute-Relation... Sample PDF
On the Cognitive Processes of Human Perception with Emotions, Motivations, and Attitudes
Chapter 5
Qingyong Li, Zhiping Shi, Zhongzhi Shi
Sparse coding theory demonstrates that the neurons in the primary visual cortex form a sparse representation of natural scenes in the viewpoint of... Sample PDF
A Selective Sparse Coding Model with Embedded Attention Mechanism
Chapter 6
Yingxu Wang
Theoretical research is predominately an inductive process, while applied research is mainly a deductive process. Both inference processes are based... Sample PDF
The Cognitive Processes of Formal Inferences
Chapter 7
Douglas Griffith, Frank L. Greitzer
The purpose of this article is to re-address the vision of human-computer symbiosis as originally expressed by J.C.R. Licklider nearly a... Sample PDF
Neo-Symbiosis: The Next Stage in the Evolution of Human Information Interaction
Chapter 8
Ray E. Jennings
Although linguistics may treat languages as a syntactic and/or semantic entity that regulates both language production and comprehension, this... Sample PDF
Language, Logic, and the Brain
Chapter 9
Yingxu Wang, Guenther Ruhe
Decision making is one of the basic cognitive processes of human behaviors by which a preferred option or a course of actions is chosen from among a... Sample PDF
The Cognitive Process of Decision Making
Chapter 10
Tiansi Dong
This chapter proposes a commonsense understanding of distance and orientation knowledge between extended objects, and presents a formal... Sample PDF
A Commonsense Approach to Representing Spatial Knowledge Between Extended Objects
Chapter 11
Natalia López, Manuel Núñez, Fernando L. Pelayo
In this chapter we present the formal language, stochastic process algebra (STOPA), to specify cognitive systems. In addition to the usual... Sample PDF
A Formal Specification of the Memorization Process
Chapter 12
Yingxu Wang
Autonomic computing (AC) is an intelligent computing approach that autonomously carries out robotic and interactive applications based on goal- and... Sample PDF
Theoretical Foundations of Autonomic Computing
Chapter 13
Witold Kinsner
Numerous attempts are being made to develop machines that could act not only autonomously, but also in an increasingly intelligent and cognitive... Sample PDF
Towards Cognitive Machines: Multiscale Measures and Analysis
Chapter 14
Amar Ramdane-Cherif
Cognitive approach through the neural network (NN) paradigm is a critical discipline that will help bring about autonomic computing (AC). NN-related... Sample PDF
Towards Autonomic Computing: Adaptive Neural Network for Trajectory Planning
Chapter 15
Lee Flax
We give an approach to cognitive modelling, which allows for richer expression than the one based simply on the firing of sets of neurons. The... Sample PDF
Cognitive Modelling Applied to Aspects of Schizophrenia and Autonomic Computing
Chapter 16
Yan Zhao, Yiyu Yao
Classification is one of the main tasks in machine learning, data mining, and pattern recognition. Compared with the extensively studied automation... Sample PDF
Interactive Classification Using a Granule Network
Chapter 17
Mehdi Najjar, André Mayers
Encouraging results of last years in the field of knowledge representation within virtual learning environments confirms that artificial... Sample PDF
A Cognitive Computational Knowledge Representation Theory
Chapter 18
Du Zhang
A crucial component of an intelligent system is its knowledge base that contains knowledge about a problem domain. Knowledge base development... Sample PDF
A Fixpoint Semantics for Rule-Base Anomalies
Chapter 19
Christine W. Chan
This chapter presents a method for ontology construction and its application in developing ontology in the domain of natural gas pipeline... Sample PDF
Development of an Ontology for an Industrial Domain
Chapter 20
Václav Rajlich, Shaochun Xu
This article explores the non-monotonic nature of the programmer learning that takes place during incremental program development. It uses a... Sample PDF
Constructivist Learning During Software Development
Chapter 21
Witold Kinsner
Many scientific chapters treat the diversity of fractal dimensions as mere variations on either the same theme or a single definition. There is a... Sample PDF
A Unified Approach to Fractal Dimensions
Chapter 22
Du Zhang, Witold Kinsner, Jeffrey Tsai, Yingxu Wang, Philip Sheu, Taehyung Wang
The 2005 IEEE International Conference on Cognitive Informatics (ICCI’05) was held during August 8th to 10th 2005 on the campus of University of... Sample PDF
Cognitive Informatics: Four Years in Practice
Chapter 23
Yiyu Yao, Zhongzhi Shi, Yingxu Wang, Witold Kinsner, Yixin Zhong, Guoyin Wang
Cognitive informatics (CI) is a cutting-edge and multidisciplinary research area that tackles the fundamental problems shared by modern informatics... Sample PDF
Toward Cognitive Informatics and Cognitive Computers: A Report on IEEE ICCI'06
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