Now showing items 1-20 of 188

    • A collaborative statistical actor-critic learning approach for 6G network slicing control 

      Rezazadeh, Farhad; Chergui, Hatim; Blanco Botana, Luis; Alonso Zárate, Luis Gonzaga; Verikoukis, Christos (Institute of Electrical and Electronics Engineers (IEEE), 2021)
      Conference lecture
      Open Access
      Artificial intelligence (AI)-driven zero-touch massive network slicing is envisioned to be a disruptive technology in beyond 5G (B5G)/6G, where tenancy would be extended to the final consumer in the form of advanced digital ...
    • A Comparison of autonomous vehicle navigation simulators under regulatory and reinforcement learning constraints 

      Cabañeros, Alex; Angulo Bahón, Cecilio (IOS Press, 2019)
      Conference lecture
      Restricted access - publisher's policy
      The transition from conventional vehicles to autonomous vehicles is regulated thorough ADAS (Advanced Driver Assistance Systems) functionalities. The combination of different ADAS functions allows vehicles navigate on a ...
    • A competitive strategy for function approximation in Q-learning 

      Agostini, Alejandro Gabriel; Celaya Llover, Enric (2011)
      Conference report
      Open Access
      In this work we propose an approach for generalization in continuous domain Reinforcement Learning that, instead of using a single function approximator, tries many different function approximators in parallel, each one ...
    • A Learning Approach to Solving Automatic Control Problems 

      Parellada Calderer, Benjami (Universitat Politècnica de Catalunya, 2022-10-18)
      Bachelor thesis
      Restricted access - author's decision
      Els problemes de control automàtic poden ser extremadament difícils de resoldre per a qualsevol algoritme no adaptatiu. El control automàtic implica l'avaluació en temps real de les respostes d'un sistema que es retroalimenta ...
    • A novel framework for dynamic spectrum management in multiCell OFDMA networks based on reinforcement learning 

      Bernardo Álvarez, Francisco; Agustí Comes, Ramon; Pérez Romero, Jordi; Sallent Roig, Oriol (2010)
      Conference report
      Open Access
      In this work the feasibility of Reinforcement Learning (RL) for Dynamic Spectrum Management (DSM) in the context of next generation multicell Orthogonal Frequency Division Multiple Access (OFDMA) networks is studied. ...
    • A reinforcement learning approach using Markov decision processes for battery energy storage control within a smart contract framework 

      Selseleh Jonban, Mansour; Romeral Martínez, José Luis; Marzband, Mousa; Abusorrah, Abdullah (Elsevier, 2024-05-10)
      Article
      Restricted access - publisher's policy
      With the increasing penetration of renewable energy sources (RESs), the necessity for employing smart methods to control and manage energy has become undeniable. This study introduces a real-time energy management system ...
    • A reinforcement learning congestion control algorithm for smart grid networks 

      Andrade Zambrano, Argenis Ronaldo; Astudillo Leon, Juan Pablo; Morocho Cayamcela, Manuel Eugenio; Lemus Cárdenas, Leticia; Cruz Llopis, Luis Javier de la (Institute of Electrical and Electronics Engineers (IEEE), 2024-05-24)
      Article
      Open Access
      Modern electrical systems are evolving with data communication networks, ushering in upgraded electrical infrastructures and enabling bidirectional communication between utility grids and consumers. The selection of ...
    • A reinforcement learning path planning approach for range-only underwater target localization with autonomous vehicles 

      Masmitjà Rusiñol, Ivan; Martín Muñoz, Mario; Katija, Kakani; Gomáriz Castro, Spartacus; Navarro Bernabé, Joan (Institute of Electrical and Electronics Engineers (IEEE), 2022)
      Conference report
      Open Access
      Underwater target localization using range-only and single-beacon (ROSB) techniques with autonomous vehicles has been used recently to improve the limitations of more complex methods, such as long baseline and ultra-short ...
    • A self-organized spectrum assignment strategy in next generation OFDMA networks providing secondary spectrum access 

      Bernardo Álvarez, Francisco; Agustí Comes, Ramon; Pérez Romero, Jordi; Sallent Roig, Oriol (2009)
      Conference report
      Open Access
      This paper proposes a Self-organized Spectrum Assignment strategy in the context of next generation multicell Orthogonal Frequency Division Multiple Access networks. The proposed strategy is able to dynamically find ...
    • A transfer reinforcement learning approach for capacity sharing in Beyond 5G networks 

      Vilà Muñoz, Irene; Pérez Romero, Jordi; Sallent Roig, Oriol (Multidisciplinary Digital Publishing Institute (MDPI), 2024-12-01)
      Article
      Open Access
      The use of Reinforcement Learning (RL) techniques has been widely addressed in the literature to cope with capacity sharing in 5G Radio Access Network (RAN) slicing. These algorithms consider a training process to learn ...
    • Adaptación de un videojuego para su uso como entorno de entrenamiento de agentes con capacidades de coordinación 

      Sancho-Tello Bayarri, Xavier (Universitat Politècnica de Catalunya, 2023-05-17)
      Bachelor thesis
      Open Access
      En este proyecto se ha realizado una búsqueda en ocho entornos que se consideraron aptos para el entrenamiento de agentes que utilicen algoritmos de aprendizaje por refuerzo en misiones de coordinación y se han analizado ...
    • Adaptación del framework Minedojo para su uso en el aprendizaje por refuerzo multiagente 

      González Reguera, Iván (Universitat Politècnica de Catalunya, 2024-01-23)
      Bachelor thesis
      Open Access
      En este proyecto se adaptará el framework MineDojo basado en Minecraft, un famoso videojuego de tipo sandbox que ofrece una gran cantidad de posibilidades, para poder realizar un entrenamiento multiagente mediante aprendizaje ...
    • Adaptive optics control with multi-agent model-free reinforcement learning 

      Pou Mulet, Bartomeu; Ferreira, Florian; Quiñones Moreno, Eduardo; Gratadour, Damien; Martín Muñoz, Mario (2022-01-14)
      Article
      Open Access
      We present a novel formulation of closed-loop adaptive optics (AO) control as a multi-agent reinforcement learning (MARL) problem in which the controller is able to learn a non-linear policy and does not need a priori ...
    • Adaptive request scheduling for the I/O forwarding layer using reinforcement learning 

      Bez, Jean Luca; Zanon Boito, Francieli; Nou Castell, Ramon; Miranda Bueno, Alberto; Cortés, Toni; Navaux, Philippe O.A. (Elsevier, 2020-11)
      Article
      Open Access
      In this paper, we propose an approach to adapt the I/O forwarding layer of HPC systems to applications’ access patterns. I/O optimization techniques can improve performance for the access patterns they were designed to ...
    • Adding agent communication in a Multi-Agent cooperative environment 

      Jaquet Rosell, Dídac (Universitat Politècnica de Catalunya, 2024-05-13)
      Bachelor thesis
      Open Access
      En els darrers anys, l'adopció d'algorismes basats en Intel·ligència Artificial (IA) ha augmentat ràpidament fins a arribar al punt que, a dia d'avui, podem veure com moltes aplicacions, fins i tot algunes que utilitzem ...
    • Agentes inteligentes para imitar el comportamiento de los jugadores de pádel 

      Lopez Rodríguez, Ivan (Universitat Politècnica de Catalunya, 2022-06-29)
      Bachelor thesis
      Open Access
      La idea principal del trabajo era la de generar una aplicación de pádel mediante Unity y su librería ML-agents. Por tanto, con la ayuda de la librería entrenaríamos distintos agentes para que aprendieran a jugar a pádel ...
    • Aircraft-to-aircraft separation based on reinforcement learning 

      Prawda, Weronika (Universitat Politècnica de Catalunya, 2022-09-12)
      Bachelor thesis
      Open Access
      Air traffic has been increasing and with it the workload of air traffic controllers. Despite the pandemic, the latest figures show a rapid recovery and forecast exponential growth. This indicates the need to modernise air ...
    • An application of explainability methods in reinforcement learning 

      Climent Muñoz, Antoni (Universitat Politècnica de Catalunya, 2020-07-02)
      Bachelor thesis
      Open Access
      La popularidad de los métodos explicativos está aumentando en el contexto de la Inteligencia Artificial y consiste en dar explicaciones inteligibles a modelos complejos. Recientemente, en el contexto del Aprendizaje Reforzado ...
    • An artificial intelligence strategy for the deployment of future microservice-based applications in 6G networks 

      Ssemakula, John Bosco; Gorricho Moreno, Juan Luis; Kibalya, Godfrey Mirondo; Serrat Fernández, Juan (Springer, 2024-03-28)
      Article
      Open Access
      Future applications to be supported by 6G networks are envisaged to be realized by loosely-coupled and independent microservices. In order to achieve an optimal deployment of applications, smart resource management strategies ...
    • An efficient RAN slicing strategy for a heterogeneous network with eMBB and V2X services 

      Resin Albonda, Haider D.; Pérez Romero, Jordi (Institute of Electrical and Electronics Engineers (IEEE), 2019-03)
      Article
      Open Access
      Emerging 5G wireless technology will support services and use cases with vastly heterogeneous requirements. Network slicing, which allows composing multiple dedicated logical networks with specific functionality running ...