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Your search keyword '"Jaime Andrés Rincón"' showing total 6 results
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6 results on '"Jaime Andrés Rincón"'

1. Application of Machine Vision Techniques in Low-Cost Devices to Improve Efficiency in Precision Farming

Author

Juan Felipe Jaramillo-Hernández, Vicente Julian, Cedric Marco-Detchart, and Jaime Andrés Rincón

Subjects
computer vision, object detection, depth estimation, precision agriculture, Chemical technology, TP1-1185
Abstract

In the context of recent technological advancements driven by distributed work and open-source resources, computer vision stands out as an innovative force, transforming how machines interact with and comprehend the visual world around us. This work conceives, designs, implements, and operates a computer vision and artificial intelligence method for object detection with integrated depth estimation. With applications ranging from autonomous fruit-harvesting systems to phenotyping tasks, the proposed Depth Object Detector (DOD) is trained and evaluated using the Microsoft Common Objects in Context dataset and the MinneApple dataset for object and fruit detection, respectively. The DOD is benchmarked against current state-of-the-art models. The results demonstrate the proposed method’s efficiency for operation on embedded systems, with a favorable balance between accuracy and speed, making it well suited for real-time applications on edge devices in the context of the Internet of things.

Published
2024
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2. Ethical Concerns and Opportunities in Binding Intelligent Systems and Blockchain Technology

Author

Calvaresi, Davide, Piguet, Jean-Gabriel, Calbimonte, Jean-Paul, Kampik, Timotheus, Najjar, Amro, Gadek, Guillaume, Schumacher, Michael, Prieta, Fernando De La, Mathieu, Philippe, Arango, Jaime Andrés Rincón, Bolock, Alia El, Val, Elena Del, Prunera, Jaume Jordán, Carneiro, João, Fuentes, Rubén, Lopes, Fernando, and Julián, Vicente

Subjects
Computer science [C05] [Engineering, computing & technology], Sciences informatiques [C05] [Ingénierie, informatique & technologie]
Published
2020

3. Highlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection : International Workshops of PAAMS 2020, L'Aquila, Italy, October 7–9, 2020, Proceedings

Author

Fernando De La Prieta, Philippe Mathieu, Jaime Andrés Rincón Arango, Alia El Bolock, Elena Del Val, Jaume Jordán Prunera, João Carneiro, Rubén Fuentes, Fernando Lopes, Vicente Julian, Fernando De La Prieta, Philippe Mathieu, Jaime Andrés Rincón Arango, Alia El Bolock, Elena Del Val, Jaume Jordán Prunera, João Carneiro, Rubén Fuentes, Fernando Lopes, and Vicente Julian

Subjects
Artificial intelligence, Application software, Computer networks, Computers, Special purpose, Electronic commerce
Abstract

This book constitutes the refereed proceedings of the workshops co-located with the 18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020, held in L'Aquila, Italy, in October 2020. The total of 21 full and 13 short papers presented in this volume were carefully reviewed and selected from 57 submissions. The papers in this volume stem from the following meetings: Workshop on Agent-Based Artificial Markets Computational Economics (ABAM); Workshop on Agents and Edge-AI (AgEdAI); Workshop on Character Computing (C2); Workshop on MAS for Complex Networks and Social Computation (CNSC); Workshop on Decision Support, Recommendation, and Persuasion in Artificial Intelligence (DeRePAI); Workshop on Multi-Agent Systems and Simulation (MAS&S); Workshop on Multi-agent based Applications for Energy Markets, Smart Grids and Sustainable Energy Systems (MASGES); Workshop on Smart Cities and Intelligent Agents (SCIA).

Published
2020

4. Extending the Framework for Developing Intelligent Virtual Environments (FIVE) with Artifacts for Modeling Internet of Things Devices and a New Decentralized Federated Learning Based on Consensus for Dynamic Networks

Author

Miguel Rebollo, Jaime Andrés Rincon, Luís Hernández, Francisco Enguix, and Carlos Carrascosa

Subjects
complex networks, distributed AI, multi-agent systems (MASs), neural networks, Chemical technology, TP1-1185
Abstract

One of the main lines of research in distributed learning in recent years is the one related to Federated Learning (FL). In this work, a decentralized Federated Learning algorithm based on consensus (CoL) is applied to Wireless Ad-hoc Networks (WANETs), where the agents communicate with other agents to share their learning model as they are available to the wireless connection range. When deploying a set of agents, it is essential to study whether all the WANET agents will be reachable before the deployment. The paper proposes to explore it by generating a simulation close to the real world using a framework (FIVE) that allows the easy development and modification of simulations based on Unity and SPADE agents. A fruit orchard with autonomous tractors is presented as a case study. The paper also presents how and why the concept of artifact has been included in the above-mentioned framework as a way to highlight the importance of some devices used in the environment that have to be located in specific places to ensure the full connection of the system. This inclusion is the first step to allow Digital Twins to be modeled with this framework, now allowing a Digital Shadow of those devices.

Published
2024
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5. A two tier architecture for Local Energy Market Simulation and Control

Author

Sandra Garcia-Rodriguez, Rui Andrade, Zita Vale, Isabel Praça, ISEP/GECAD, Intelligence Artificielle et Apprentissage Automatique (LI3A), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, This work has received funding from National Funds through FCT (Fundaçao da Ciencia e Tecnologia) under the project SPET – 29165, call SAICT 2017, Fernando De La Prieta, Philippe Mathieu, Jaime Andrés Rincón Arango, Alia El Bolock, Elena Del Val, Jaume Jordán Prunera, João Carneiro, Rubén Fuentes, Fernando Lopes, Vicente Julian, and Repositório Científico do Instituto Politécnico do Porto

Subjects
Optimization, Energy management, Computer science, 020209 energy, Distributed computing, media_common.quotation_subject, Control (management), 02 engineering and technology, data monitoring, Negotiation, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], modelling, online: 978-3-030-51999-5 Print ISBN 978-3-030-51998-8, multi-agent system, 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY], Energy market, Layer (object-oriented design), rust Evaluation, media_common, Energy, Trustworthy Artificial intelligence, Multitier architecture, Multi-agent system, Multi-agent systems, artificial intelligence, simulation, machine learning, Work (electrical), [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], [SDE]Environmental Sciences, 020201 artificial intelligence & image processing, distributed learning, Forecasting
Abstract

This paper addresses energy management and security having as basis sensing and monitoring of cyber-physical infrastructure of consumers and prosumers, and their participation in the Local Energy Market (LEM). The vision is to create a layered multi-agent framework that brings a complete view of the cyber-physical system of LEM participants, and provides optimization and control of energy for said participants. The proposed system is separated into a Market layer and a Cyber-Physical layer, each of them providing different services. The cyber-physical layer, represented by SMARTERCtrol system, provides Data Monitoring and Optimized Energy Control of individual building resources. The Market layer, represented by LEM Multi-Agent System, provides Negotiation, Forecasting, and Trust Evaluation. Both systems work together to provide and integrate a tool for simulation and control of LEM., This work has received funding from National Funds through FCT (Fundaçao da Ciencia e Tecnologia) under the project SPET – 29165, call SAICT 2017.

Published
2020
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6. Multi-agents Ultimatum Game with Reinforcement Learning

Author

Benoit Radier, Tangui Le Gleau, Tayeb Lemlouma, Xavier Marjou, Orange Labs [Lannion], France Télécom, Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), RÉSEAUX, TÉLÉCOMMUNICATION ET SERVICES (IRISA-D2), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Objets communicants pour l'Internet du futur (OCIF), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-RÉSEAUX, TÉLÉCOMMUNICATION ET SERVICES (IRISA-D2), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Fernando De La Prieta, Philippe Mathieu, Jaime Andrés Rincón Arango, Alia El Bolock, Elena Del Val, Jaume Jordán Prunera, João Carneiro, Rubén Fuentes, Fernando Lopes, Vicente Julian, Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), IMT Atlantique (IMT Atlantique), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)

Subjects
Computer science, media_common.quotation_subject, Multi-agents systems, Artificial neural network model, 02 engineering and technology, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], 020204 information systems, Voting, 0202 electrical engineering, electronic engineering, information engineering, Reinforcement learning, Game theory, media_common, Ultimatum game, [INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], business.industry, Pirate game, Experimental economics, Reinforcement Learning, Iterated function, [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], 020201 artificial intelligence & image processing, Artificial intelligence, business
Abstract

International Workshops of PAAMS 2020, L'Aquila, Italy, October 7–9, 2020, Proceedings; International audience; The Ultimatum Game is an experimental economics game in which an agent has to propose a sharing partition of a limited amount of resources to other agents who have to accept it or not. If the offer is rejected per consensus, the process of sharing is abandoned. So all agents have to guess what are the best decisions (offer and vote) to optimise their respective gain. We focus on an iterated multi-agent version of Ultimatum Game also known as the Pirate Game, a riddle in which pirates have to share coins according to specific rules. To solve such game, we employ a multi-agent model. In particular, we design a new kind of Artificial Neural Network model able to output an integer partition of discrete finite resources, trained by a Reinforcement Learning agent to identify an acceptable offer to the voting agents. We take an interest in evaluating the performances against several kinds of voting behaviours. The results are close to theoretical optima for all tested scenarios thus demonstrating the flexibility of our method.

Published
2020
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