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Artificial intelligence tools for academic management: assigning students to academic supervisors
(International Academy of Technology, Education and Development (IATED), 2020)
In the last few years, there has been a broad range of research focusing on how learning should take place both in the classroom and outside the classroom. Even though academic dissertations are a vital step in the academic ...
Predicting shuttle arrival time in istanbul
(Springer Nature, 2020)
Nowadays, transportation companies look for smart solutions in order to improve quality of their services. Accordingly, an intercity bus company in Istanbul aims to improve their shuttle schedules. This paper proposes ...
Not all mistakes are equal
(The ACM Digital Library, 2020)
In many tasks, classifiers play a fundamental role in the way an agent behaves. Most rational agents collect sensor data from the environment, classify it, and act based on that classification. Recently, deep neural networks ...
Taking inventory changes into account while negotiating in supply chain management
(SciTePress, 2020)
In a supply chain environment, supply chain entities need to make joint decisions on the transaction of goods under the issues quantity, delivery time and unit price in order to procure/sell goods at right quantities and ...
Towards automated aircraft maintenance inspection. A use case of detecting aircraft dents using mask r-cnn
(American Institute of Aeronautics and Astronautics Inc, AIAA, 2020)
Deep learning can be used to automate aircraft maintenance visual inspection. This can help increase the accuracy of damage detection, reduce aircraft downtime, and help prevent inspection accidents. The objective of this ...
ANAC 2018: Repeated multilateral negotiation league
(Springer, 2020)
This is an extension from a selected paper from JSAI2019. There are a number of research challenges in the field of Automated Negotiation. The Ninth International Automated Negotiating Agent Competition encourages participants ...
Campaign participation prediction with deep learning
(Elsevier, 2021-08)
Increasingly, on-demand nature of customer interactions put pressure on companies to build real-time campaign management systems. Instead of having managers to decide on the campaign rules, such as, when, how and whom to ...
Would you imagine yourself negotiating with a robot, Jennifer? Why not?
(IEEE, 2022-02)
With the improvement of intelligent systems and robotics, social robots are becoming part of our society. To accomplish complex tasks, robots and humans may need to collaborate, and when necessary, they need to negotiate ...
Misclassification risk and uncertainty quantification in deep classifiers
(IEEE, 2021)
In this paper, we propose risk-calibrated evidential deep classifiers to reduce the costs associated with classification errors. We use two main approaches. The first is to develop methods to quantify the uncertainty of a ...
EXPECTATION: Personalized explainable artificial intelligence for decentralized agents with heterogeneous knowledge
(Springer, 2021)
Explainable AI (XAI) has emerged in recent years as a set of techniques and methodologies to interpret and explain machine learning (ML) predictors. To date, many initiatives have been proposed. Nevertheless, current ...
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