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Tamim Mahmud Al-Hasan, Aya Nabil Sayed, Faycal Bensaali, Yassine Himeur, Iraklis Varlamis and George Dimitrakopoulos
Recommender systems are a key technology for many applications, such as e-commerce, streaming media, and social media. Traditional recommender systems rely on collaborative filtering or content-based filtering to make recommendations. However, these appr...
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Gelsomina Manganiello, Nicola Nicastro, Luciano Ortenzi, Federico Pallottino, Corrado Costa and Catello Pane
Fusarium oxysporum f. sp. lactucae is one of the most aggressive baby-lettuce soilborne pathogens. The application of Trichoderma spp. as biocontrol agents can minimize fungicide treatments and their effective targeted use can be enhanced by support of d...
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Abdullahi T. Sulaiman, Habeeb Bello-Salau, Adeiza J. Onumanyi, Muhammed B. Mu?azu, Emmanuel A. Adedokun, Ahmed T. Salawudeen and Abdulfatai D. Adekale
The particle swarm optimization (PSO) algorithm is widely used for optimization purposes across various domains, such as in precision agriculture, vehicular ad hoc networks, path planning, and for the assessment of mathematical test functions towards ben...
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Pedro Almeida, Vitor Carvalho and Alberto Simões
Reinforcement Learning is one of the many machine learning paradigms. With no labelled data, it is concerned with balancing the exploration and exploitation of an environment with one or more agents present in it. Recently, many breakthroughs have been m...
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Yujie Wei, Hongpeng Zhang, Yuan Wang and Changqiang Huang
Maneuver decision-making is essential for autonomous air combat. However, previous methods usually make decisions to aim at the target instead of hitting the target and use discrete action spaces instead of continuous action spaces. While these simplific...
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Sara de Freitas, Victoria Uren, Kristian Kiili, Manuel Ninaus, Panagiotis Petridis, Petros Lameras, Ian Dunwell, Sylvester Arnab, Stephen Jarvis and Kam Star
Feedback is a critical aspect of optimised learning design, but there are few, if any, feedback models that map different types of feedback and how they may assist students to increase performance and enhance their learning experience. This research pape...
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Yoshinari Motokawa and Toshiharu Sugawara
In this paper, we propose an enhanced version of the distributed attentional actor architecture (eDA3-X) for model-free reinforcement learning. This architecture is designed to facilitate the interpretability of learned coordinated behaviors in multi-age...
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Saad Awadh Alanazi, Maryam Shabbir, Nasser Alshammari, Madallah Alruwaili, Iftikhar Hussain and Fahad Ahmad
The research area falls under the umbrella of affective computing and seeks to introduce intelligent agents by simulating emotions artificially and encouraging empathetic behavior in them, to foster emotional empathy in intelligent agents with the overar...
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Raphael C. Engelhardt, Marc Oedingen, Moritz Lange, Laurenz Wiskott and Wolfgang Konen
The demand for explainable and transparent models increases with the continued success of reinforcement learning. In this article, we explore the potential of generating shallow decision trees (DTs) as simple and transparent surrogate models for opaque d...
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Szabolcs Deák, Paul Levine, Joseph Pearlman and Bo Yang
We construct a New Keynesian (NK) behavioural macroeconomic model with bounded-rationality (BR) and heterogeneous agents. We solve and simulate the model using a third-order approximation for a given policy and evaluate its properties using this solution...
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