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What is DRL

Fostering Cross-Industry Sustainability With Intelligent Technologies
Deep reinforcement learning.
Published in Chapter:
AI-Based Education for Sustainability and the Promotion of Lifestyle and Healthy Diet
Sami Fattouch (National Institute of Applied Sciences and Technology (INSAT), University of Carthage (UCAR), Tunis, Tunisia), Fethi Ben Slama (Ecole Supérieure des Sciences et Techniques de la Santé de Tunis, University Tunis El Manar (UTM), Tunisia), Henda Jamoussi (National Institute of Nutrition and Food Technology, Tunisia), and Luana Bontempo (Fondazione Edmund Mach, Italy)
DOI: 10.4018/979-8-3693-1638-2.ch006
The literature is prolific in studies about the artificial intelligence (AI) applications, particularly to support formal education and develop adaptive lifelong learning environments by means of an array of flexible, inclusive, and interactive tools. AI-based education is assumed to be determinant for the achievement of the Sustainable Development Goals (SDGs), targeted for 2030, and supported by all 193 member states of the United Nations. This intelligent technology is expected to play a key role to raising awareness about the management of food discards and byproducts for a circular economy, thus optimizing the resources' efficiency and slowing down their economic, social, and environmental impacts. This chapter provides an overview of the AI applications and challenges to promote sustainable food habits and to monitor and manage local food byproducts suitable for human consumption to develop nutritional and healthy added-value outcomes.
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DRL-Based Coverage Optimization in UAV Networks for Microservice-Based IoT Applications
(Deep Reinforcement Learning): A branch of machine learning that combines deep learning algorithms with the reinforcement learning approach, where an agent learns to make optimal decisions through interaction with an environment and receiving rewards or penalties for its actions.
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