Related papers: Reducing Student Distraction Through Fuzzy Logic B…
Fuzzy c-means based clustering algorithms are frequently used for Takagi-Sugeno-Kang (TSK) fuzzy classifier antecedent parameter estimation. One rule is initialized from each cluster. However, most of these clustering algorithms are…
Classical notions of disjunctive and cumulative scheduling are studied from the point of view of soft constraint satisfaction. Soft disjunctive scheduling is introduced as an instance of soft CSP and preferences included in this problem are…
Combining symbolic and neural approaches has gained considerable attention in the AI community, as it is often argued that the strengths and weaknesses of these approaches are complementary. One such trend in the literature are weakly…
Class Scheduling is a highly constrained task. Educational institutes spend a lot of resources, in the form of time and manual computation, to find a satisficing schedule that fulfills all the requirements. A satisficing class schedule…
Fuzzy controllers have gained popularity in the past few decades with successful implementations in many fields that have enabled designers to control complex systems through linguistic-based rules in contrast to traditional methods. This…
The flock-guidance problem enjoys a challenging structure where multiple optimization objectives are solved simultaneously. This usually necessitates different control approaches to tackle various objectives, such as guidance, collision…
Studies on software tutoring systems for complex learning have shown that confusion has a beneficial relationship with the learning experience and student engagement (Arguel et al., 2017). Causing confusion can prevent boredom while signs…
We present a unified logical framework for representing and reasoning about both quantitative and qualitative preferences in fuzzy answer set programming, called fuzzy answer set optimization programs. The proposed framework is vital to…
Logics with analogous semantics, such as Fuzzy Logic, have a number of explanatory and application advantages, the most well-known being the ability to help experts develop control systems. From a cognitive systems perspective, such…
... This paper is to describe exploratory research on the design of a modular autonomous mobile robot controller. The controller incorporates a fuzzy logic [8] [9] approach for steering and speed control [37], a FL approach for ultrasound…
Federated learning is an important framework in modern machine learning that seeks to integrate the training of learning models from multiple users, each user having their own local data set, in a way that is sensitive to data privacy and…
The current article discusses some applications of fuzzy logic to assessment of learning. We consider here a new trapezoidal fuzzy model for learning assessment.
The analysis of remote discussions is not yet at the same level as the face-to-face ones. The present paper aspires twofold. On the one hand, it attempts to establish a suitable environment of interaction and collaboration among learners by…
In this paper, we have gone through different AI-Based frameworks used for various educational tasks like digital customized assignment allotment and performance monitoring, identifying slow-learners and fast-learners, etc. application…
Label learning is a fundamental task in machine learning that aims to construct intelligent models using labeled data, encompassing traditional single-label and multi-label classification models. Traditional methods typically rely on…
Academic procrastination is a persistent challenge in computing education, yet evidence on the effectiveness of course-level interventions remains fragmented across diverse designs and contexts. We present a systematic literature review of…
Time series clustering is an essential machine learning task with applications in many disciplines. While the majority of the methods focus on time series taking values on the real line, very few works consider time series defined on the…
Many studies have found active learning, either in the form of in-class exercises or projects, to be superior to traditional lectures. However, these forms of hands-on learning do not always lead students to reach the higher order thinking…
The integration of fuzzy set theory and fuzzy logic into scheduling is a rather new aspect with growing importance for manufacturing applications, resulting in various unsolved aspects. In the current paper, we investigate an improved local…
This paper introduces an evaluation methodologies for the e-learners' behaviour that will be a feedback to the decision makers in e-learning system. Learner's profile plays a crucial role in the evaluation process to improve the e-learning…