Now showing items 1-20 of 106

    • 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 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 ...
    • 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 ...
    • 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 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 ...
    • Analysis of RAN slicing for cellular V2X and mobile broadband services based on reinforcement learning 

      Albonda, Haider Daami Resin; Pérez Romero, Jordi (European Alliance for Innovation n.o., 2020-03)
      Article
      Open Access
      Radio Access Network (RAN) slicing is one of the key enablers to provide the design flexibility and enable 5G system to support heterogeneous services over a common platform (i.e., by creating a customized slice for each ...
    • Applying and verifying an explainability method based on policy graphs in the context of reinforcement learning 

      Climent Muñoz, Antoni; Gnatyshak, Dmitry; Álvarez Napagao, Sergio (IOS Press, 2021)
      Conference report
      Open Access
      The advancement on explainability techniques is quite relevant in the field of Reinforcement Learning (RL) and its applications can be beneficial for the development of intelligent agents that are understandable by humans ...
    • Applying multi-agent reinforcement learning to solve sequential moral dilemmas 

      Choinski, Michal (Universitat Politècnica de Catalunya, 2021-04-26)
      Master thesis
      Open Access
      Covenantee:   Universitat de Barcelona. Facultat de Matemàtiques i Informàtica / Universitat Rovira i Virgili
      Incorporation of ethical values in the field of Artificial Intelligence is inevitable. With the rapid development of technologies capable of making autonomous decisions, more attention should be dedicated to the process ...
    • Applying the rainbow architecture to intrusion detection systems 

      Izquierdo García-Faria, Tomás (Universitat Politècnica de Catalunya, 2021-04-28)
      Master thesis
      Open Access
      There is a lot of expectation on how Artificial Intelligence (AI) is going to have an impact on Cybersecurity. From new sophisticated attacks to new ways of defending a system from cybercriminals. A lot of techniques are ...
    • Aprendizaje por refuerzo aplicado a los videojuegos cooperativos 

      Alcocer Soto, Daniel (Universitat Politècnica de Catalunya, 2018-07)
      Bachelor thesis
      Open Access
      Se ha desarrollado un algoritmo que combina el uso de redes neuronales con el algoritmo Q-learning para aprender a jugar con la ayuda de un jugador humano y aprender a cooperar con él para ganar en un videojuego basado en ...
    • Aprendizaje por refuerzo aplicado a personajes no controlables en Minetest 

      Romero Reviriego, Aitor (Universitat Politècnica de Catalunya, 2019-01)
      Bachelor thesis
      Open Access
      En este proyecto se ha utilizado la rama de la IA llamada aprendizaje por refuerzo y intenta desarrollar agentes para el videojuego Minetest que actúen como aliados del jugador.
    • Aprendizaje por refuerzo multi-nivel para sistemas RRM 

      Collados Zamora, Kevin (Universitat Politècnica de Catalunya, 2014-03-17)
      Master thesis (pre-Bologna period)
      Open Access
      [ANGLÈS] This paper focuses on the problem of resource management in the field of RRM (Radio Resource Management) systems with more than one objective to maximize. Specifically focuses on simultaneously maximize the quality ...