Adina Cocu | University Dunarea de Jos of Galati (original) (raw)
Papers by Adina Cocu
BRAIN. Broad Research in Artificial Intelligence and Neuroscience , 2024
The paper discusses the prospects and risks associated with the development superintelligent arti... more The paper discusses the prospects and risks associated with the development superintelligent artificial intelligence (AI) and artificial consciousness (AC) ten years after Nick Bostrom explored these ideas in his influential book (Bostrom, 2014). We argue that the debate about the evolution of AI has changed at least in the following aspects: First, the development of superintelligent machines is no longer limited to speculations about a distant future – recent advances in this field already produce immediate and palpable impact across various sectors, including education, business, and technology. Second, we argue that the debate on whether AI systems might one day achieve a form of artificial consciousness (AC) has shifted from a theoretical possibility to a pressing concern. After reviewing some of the most likely prerequisites for the development of potentially dangerous AI systems, we suggest several directions of action to avoid the risk of losing control over superintelligent AI.
ICERI proceedings, Nov 1, 2022
Lecture notes in networks and systems, 2023
2017 IEEE Global Engineering Education Conference (EDUCON), 2017
The students' creativity and “integrative thinking” are highly valued qualities in the modern... more The students' creativity and “integrative thinking” are highly valued qualities in the modern education. But is there any connection between them? This paper describes a simple experiment aimed to explore the possible connection and mutual influence between the students' creativity and their ability to summarize the main ideas from a given text. The overall creativity of the students who participated in the experiment was assessed by means of a previoulsly developped dedicated software tool. Besides that, their summary writing skills were assessed by a panel of 3 experts, and the scores were normalized to the interval [0-100]. Preliminary experimental data show a good correlation between the creativity quotient CQ and the ability of the students to extract and communicate the main ideas from a written text. Further research is in progress.
ICERI proceedings, Nov 1, 2022
The European Proceedings of Social and Behavioural Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution-No... more This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 4.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper describes an experiment aimed to evaluate the influence of the environment in an "... more This paper describes an experiment aimed to evaluate the influence of the environment in an "iLab" (Innovation Laboratory) on the divergent thinking of a group of students. The philosophy behind the concept of iLab starts from the assumption that the convergent influence of an "extraordinary environment", a special communication application, and appropriate moderation techniques is capable to foster the creativity of the participants, and to enable a certain "collective intelligence". In our experiment, the group of 20 students was assigned the task to find as many new ideas as possible of ICT solutions for improving the quality of life of people with various disabilities. The ideas produced during the session were recorded and analyzed in terms of originality, feasibility, and utility using the FCA (Formal Concept Analysis) methodology. This paper presents the results of the experiment.
Analele Universităţii "Dunărea de Jos" Galaţi: Fascicula III, Electrotehnică, Electronică, Automatică, Informatică, 2008
Learning a Bayesian network from a numeric set of data is a challenging task because of dual natu... more Learning a Bayesian network from a numeric set of data is a challenging task because of dual nature of learning process: initial need to learn network structure, and then to find out the distribution probability tables. In this paper, we propose a machine-learning algorithm based on hill climbing search combined with Tabu list. The aim of learning process is to discover the best network that represents dependences between nodes. Another issue in machine learning procedure is handling numeric attributes. In order to do that, we must perform an attribute discretization pre-processes. This discretization operation can influence the results of learning network structure. Therefore, we make a comparative study to find out the most suitable combination between discretization method and learning algorithm, for a specific data set.
In this paper, a possibilistic network implementation for uncertain knowledge modeling of the dia... more In this paper, a possibilistic network implementation for uncertain knowledge modeling of the diagnostic process is proposed as a means to achieve student diagnosis in intelligent tutoring system. This approach is proposed in the object oriented programming domain for diagnosis of students learning errors and misconception. In this expertise domain dependencies between data exist that are encoded in the structure of network. Also, it is available qualitative information about these data which are represented and interpreted with qualitative approach of possibility theory. The aim of student diagnosis system is to ensure an adapted support for the student and to sustain the student in personalized learning process and errors explanation.
In intelligent tutoring systems, student or user modeling implies dealing with imperfect and unce... more In intelligent tutoring systems, student or user modeling implies dealing with imperfect and uncertain knowledge. One of the artificial intelligence techniques used for uncertainty management is that of Bayesian networks. This paradigm is recommended in the situation when exist dependencies between data and qualitative information about these data. In this work we present a student knowledge diagnosis model based on representation with Bayesian networks. The educational system incorporate a multimedia interface for accomplishes the testing tools. The results of testing sessions are represented and interpreted with probability theory in order to ensure an adapted support for the student. The aims of the computer assisted application that contains this diagnose module are to support the student in personalized learning process and errors explanation.
Abstract: Intelligent educational systems are knowledge-based systems (KBS) they can be developed... more Abstract: Intelligent educational systems are knowledge-based systems (KBS) they can be developed by a generic knowledge-based system development methodology. In this paper, we present an ontology-based approach for formalizing different knowledge types. The formalism is based upon conceptual graphs. A priority concern to all research work in adaptive education is that of finding an appropriate representation for pedagogical knowledge. For implementation, we use the CoGITaNT environment (Conceptual Graphs Integrated Tools allowing Nested Typed graphs), a library of C++ classes (open-sources, developed by LIRMM CNRS, France) allowing the development of applications based on the CG knowledge representation scheme.
Abstract: This paper presents a knowledge learning diagnostic approach implemented in an educatio... more Abstract: This paper presents a knowledge learning diagnostic approach implemented in an educational system. Probabilistic inference is used here to diagnose knowledge understanding level and to reason about probable cause of learner’s misconceptions. When one learner takes an assessment, the system use probabilistic reasoning and will advice the learner about the most appropriate error cause and will also provide, the conforming part of theory which treats errors related to his misconceptions.
Abstract: In intelligent tutoring systems, student or user modeling implies dealing with imperfec... more Abstract: In intelligent tutoring systems, student or user modeling implies dealing with imperfect and uncertain knowledge. One of the artificial intelligence techniques used for uncertainty management is that of Bayesian networks. This paradigm is recommended in the situation when exist dependencies between data and qualitative information about these data. In this work we present a student knowledge diagnosis model based on representation with Bayesian networks. The educational system incorporate a multimedia interface for accomplishes the testing tools. The results of testing sessions are represented and interpreted with probability theory in order to ensure an adapted support for the student. The aims of the computer assisted application that contains this diagnose module are to support the student in personalized learning process and errors explanation.
Abstract: In this paper, a possibilistic network implementation for uncertain knowledge modeling ... more Abstract: In this paper, a possibilistic network implementation for uncertain knowledge modeling of the diagnostic process is proposed as a means to achieve student diagnosis in intelligent tutoring system. This approach is proposed in the object oriented programming domain for diagnosis of students learning errors and misconception. In this expertise domain dependencies between data exist that are encoded in the structure of network. Also, it is available qualitative information about these data which are represented and interpreted with qualitative approach of possibility theory. The aim of student diagnosis system is to ensure an adapted support for the student and to sustain the student in personalized learning process and errors explanation.
… Systems, 2006 3rd …, 2006
Applied Sciences
As the world population is ageing rapidly and old age comes with multiple health issues, the need... more As the world population is ageing rapidly and old age comes with multiple health issues, the need for medical services is likely to increase in a couple of decades beyond the limits of the medical systems of almost any country. In response to this trend, a variety of technologies have been developed with the aim of helping older people live independently as long as possible and reduce the burden on caregivers. In this paper, we propose a solution to encode the information about the activity of the monitored person, captured by a set of binary sensors, in the form of activity maps that reflect not only the intensity, but also the spatial distribution of the activity between a set of behaviorally meaningful places. Then, we propose a method for automatic analysis of the activity maps in order to detect deviations from the previously recorded routine. We have tested the method on two public activity recognition datasets and found that the proposed solution is not only feasible, but als...
Intelligent educational systems are knowledge-based systems (KBS) they can be developed by a gene... more Intelligent educational systems are knowledge-based systems (KBS) they can be developed by a generic knowledge-based system development methodology. In this paper, we present an ontology-based approach for formalizing different knowledge types. The formalism is based upon conceptual graphs. A priority concern to all research work in adaptive education is that of finding an appropriate representation for pedagogical knowledge. For implementation, we use the CoGITaNT environment (Conceptual Graphs Integrated Tools allowing Nested Typed graphs), a library of C++ classes (open-sources, developed by LIRMM CNRS, France) allowing the development of applications based on the CG knowledge representation scheme.
BRAIN. Broad Research in Artificial Intelligence and Neuroscience , 2024
The paper discusses the prospects and risks associated with the development superintelligent arti... more The paper discusses the prospects and risks associated with the development superintelligent artificial intelligence (AI) and artificial consciousness (AC) ten years after Nick Bostrom explored these ideas in his influential book (Bostrom, 2014). We argue that the debate about the evolution of AI has changed at least in the following aspects: First, the development of superintelligent machines is no longer limited to speculations about a distant future – recent advances in this field already produce immediate and palpable impact across various sectors, including education, business, and technology. Second, we argue that the debate on whether AI systems might one day achieve a form of artificial consciousness (AC) has shifted from a theoretical possibility to a pressing concern. After reviewing some of the most likely prerequisites for the development of potentially dangerous AI systems, we suggest several directions of action to avoid the risk of losing control over superintelligent AI.
ICERI proceedings, Nov 1, 2022
Lecture notes in networks and systems, 2023
2017 IEEE Global Engineering Education Conference (EDUCON), 2017
The students' creativity and “integrative thinking” are highly valued qualities in the modern... more The students' creativity and “integrative thinking” are highly valued qualities in the modern education. But is there any connection between them? This paper describes a simple experiment aimed to explore the possible connection and mutual influence between the students' creativity and their ability to summarize the main ideas from a given text. The overall creativity of the students who participated in the experiment was assessed by means of a previoulsly developped dedicated software tool. Besides that, their summary writing skills were assessed by a panel of 3 experts, and the scores were normalized to the interval [0-100]. Preliminary experimental data show a good correlation between the creativity quotient CQ and the ability of the students to extract and communicate the main ideas from a written text. Further research is in progress.
ICERI proceedings, Nov 1, 2022
The European Proceedings of Social and Behavioural Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution-No... more This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 4.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper describes an experiment aimed to evaluate the influence of the environment in an "... more This paper describes an experiment aimed to evaluate the influence of the environment in an "iLab" (Innovation Laboratory) on the divergent thinking of a group of students. The philosophy behind the concept of iLab starts from the assumption that the convergent influence of an "extraordinary environment", a special communication application, and appropriate moderation techniques is capable to foster the creativity of the participants, and to enable a certain "collective intelligence". In our experiment, the group of 20 students was assigned the task to find as many new ideas as possible of ICT solutions for improving the quality of life of people with various disabilities. The ideas produced during the session were recorded and analyzed in terms of originality, feasibility, and utility using the FCA (Formal Concept Analysis) methodology. This paper presents the results of the experiment.
Analele Universităţii "Dunărea de Jos" Galaţi: Fascicula III, Electrotehnică, Electronică, Automatică, Informatică, 2008
Learning a Bayesian network from a numeric set of data is a challenging task because of dual natu... more Learning a Bayesian network from a numeric set of data is a challenging task because of dual nature of learning process: initial need to learn network structure, and then to find out the distribution probability tables. In this paper, we propose a machine-learning algorithm based on hill climbing search combined with Tabu list. The aim of learning process is to discover the best network that represents dependences between nodes. Another issue in machine learning procedure is handling numeric attributes. In order to do that, we must perform an attribute discretization pre-processes. This discretization operation can influence the results of learning network structure. Therefore, we make a comparative study to find out the most suitable combination between discretization method and learning algorithm, for a specific data set.
In this paper, a possibilistic network implementation for uncertain knowledge modeling of the dia... more In this paper, a possibilistic network implementation for uncertain knowledge modeling of the diagnostic process is proposed as a means to achieve student diagnosis in intelligent tutoring system. This approach is proposed in the object oriented programming domain for diagnosis of students learning errors and misconception. In this expertise domain dependencies between data exist that are encoded in the structure of network. Also, it is available qualitative information about these data which are represented and interpreted with qualitative approach of possibility theory. The aim of student diagnosis system is to ensure an adapted support for the student and to sustain the student in personalized learning process and errors explanation.
In intelligent tutoring systems, student or user modeling implies dealing with imperfect and unce... more In intelligent tutoring systems, student or user modeling implies dealing with imperfect and uncertain knowledge. One of the artificial intelligence techniques used for uncertainty management is that of Bayesian networks. This paradigm is recommended in the situation when exist dependencies between data and qualitative information about these data. In this work we present a student knowledge diagnosis model based on representation with Bayesian networks. The educational system incorporate a multimedia interface for accomplishes the testing tools. The results of testing sessions are represented and interpreted with probability theory in order to ensure an adapted support for the student. The aims of the computer assisted application that contains this diagnose module are to support the student in personalized learning process and errors explanation.
Abstract: Intelligent educational systems are knowledge-based systems (KBS) they can be developed... more Abstract: Intelligent educational systems are knowledge-based systems (KBS) they can be developed by a generic knowledge-based system development methodology. In this paper, we present an ontology-based approach for formalizing different knowledge types. The formalism is based upon conceptual graphs. A priority concern to all research work in adaptive education is that of finding an appropriate representation for pedagogical knowledge. For implementation, we use the CoGITaNT environment (Conceptual Graphs Integrated Tools allowing Nested Typed graphs), a library of C++ classes (open-sources, developed by LIRMM CNRS, France) allowing the development of applications based on the CG knowledge representation scheme.
Abstract: This paper presents a knowledge learning diagnostic approach implemented in an educatio... more Abstract: This paper presents a knowledge learning diagnostic approach implemented in an educational system. Probabilistic inference is used here to diagnose knowledge understanding level and to reason about probable cause of learner’s misconceptions. When one learner takes an assessment, the system use probabilistic reasoning and will advice the learner about the most appropriate error cause and will also provide, the conforming part of theory which treats errors related to his misconceptions.
Abstract: In intelligent tutoring systems, student or user modeling implies dealing with imperfec... more Abstract: In intelligent tutoring systems, student or user modeling implies dealing with imperfect and uncertain knowledge. One of the artificial intelligence techniques used for uncertainty management is that of Bayesian networks. This paradigm is recommended in the situation when exist dependencies between data and qualitative information about these data. In this work we present a student knowledge diagnosis model based on representation with Bayesian networks. The educational system incorporate a multimedia interface for accomplishes the testing tools. The results of testing sessions are represented and interpreted with probability theory in order to ensure an adapted support for the student. The aims of the computer assisted application that contains this diagnose module are to support the student in personalized learning process and errors explanation.
Abstract: In this paper, a possibilistic network implementation for uncertain knowledge modeling ... more Abstract: In this paper, a possibilistic network implementation for uncertain knowledge modeling of the diagnostic process is proposed as a means to achieve student diagnosis in intelligent tutoring system. This approach is proposed in the object oriented programming domain for diagnosis of students learning errors and misconception. In this expertise domain dependencies between data exist that are encoded in the structure of network. Also, it is available qualitative information about these data which are represented and interpreted with qualitative approach of possibility theory. The aim of student diagnosis system is to ensure an adapted support for the student and to sustain the student in personalized learning process and errors explanation.
… Systems, 2006 3rd …, 2006
Applied Sciences
As the world population is ageing rapidly and old age comes with multiple health issues, the need... more As the world population is ageing rapidly and old age comes with multiple health issues, the need for medical services is likely to increase in a couple of decades beyond the limits of the medical systems of almost any country. In response to this trend, a variety of technologies have been developed with the aim of helping older people live independently as long as possible and reduce the burden on caregivers. In this paper, we propose a solution to encode the information about the activity of the monitored person, captured by a set of binary sensors, in the form of activity maps that reflect not only the intensity, but also the spatial distribution of the activity between a set of behaviorally meaningful places. Then, we propose a method for automatic analysis of the activity maps in order to detect deviations from the previously recorded routine. We have tested the method on two public activity recognition datasets and found that the proposed solution is not only feasible, but als...
Intelligent educational systems are knowledge-based systems (KBS) they can be developed by a gene... more Intelligent educational systems are knowledge-based systems (KBS) they can be developed by a generic knowledge-based system development methodology. In this paper, we present an ontology-based approach for formalizing different knowledge types. The formalism is based upon conceptual graphs. A priority concern to all research work in adaptive education is that of finding an appropriate representation for pedagogical knowledge. For implementation, we use the CoGITaNT environment (Conceptual Graphs Integrated Tools allowing Nested Typed graphs), a library of C++ classes (open-sources, developed by LIRMM CNRS, France) allowing the development of applications based on the CG knowledge representation scheme.