Essays about: "förstärkningslärande"

Showing result 1 - 5 of 15 essays containing the word förstärkningslärande.

  1. 1. Explainable Reinforcement Learning for Risk Mitigation in Human-Robot Collaboration Scenarios

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Alessandro Iucci; [2021]
    Keywords : Explainable Reinforcement Learning; Human-Robot Collaboration; Risk Mitigation; Reward Decomposition; Autonomous Policy Explanation; Collaborative Robots; Förklarbar förstärkningslärande; Mänskligt-robot-samarbete; Riskreducering; Reward Decomposition; Autonomous Policy Explanation; Samarbetsrobotar;

    Abstract : Reinforcement Learning (RL) algorithms are highly popular in the robotics field to solve complex problems, learn from dynamic environments and generate optimal outcomes. However, one of the main limitations of RL is the lack of model transparency. This includes the inability to provide explanations of why the output was generated. READ MORE

  3. 2. Implementing a Control Strategy for a Cable-­driven Ankle Exoskeleton

    University essay from KTH/Maskinkonstruktion (Avd.)

    Author : Yu Zhu; [2021]
    Keywords : Cable­driven ankle exoskeleton; Torque control; Wearable robotics; Drop foot; Kabeldriven ankel exoskelet; vridmomentkontroll; bärbar robotik; fallfot;

    Abstract : Ankle exoskeletons are designed to help people with movement weakness to restore the walking ability . However, people with gait pathology, for instance, drop foot, usually have difficulties in lifting the front part of foot during gait. READ MORE

  4. 3. Bayesian Reinforcement Learning Methods for Network Intrusion Prevention

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Antonio Frederico Nesti Lopes; [2021]
    Keywords : Network Security; Reinforcement Learning; Bayesian Q-Learning; Bayesian Policy Gradient; Bayesian Actor-Critic; Markov Security Games; Nätverkssäkerhet; förstärkningslärande; Bayesian Q-Learning; Bayesian Policy Gradient; Bayesian Actor-Critic; Markov Security Games;

    Abstract : A growing problem in network security stems from the fact that both attack methods and target systems constantly evolve. This problem makes it difficult for human operators to keep up and manage the security problem. READ MORE

  5. 4. AI-driven admission control : with Deep Reinforcement Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Lingling Ai; [2021]
    Keywords : Admission Control; Reinforcement Learning; Configurable Observability; Network Slicing; Deep Q-Learning; Antagningskontroll; förstärkningsinlärning; konfigurerbar observerbarhet; nätverksdelning; Deep Q-Learning;

    Abstract : 5G is expected to provide a high-performance and highly efficient network to prominent industry verticals with ubiquitous access to a wide range of services with orders of magnitude of improvement over 4G. Network slicing, which allocates network resources according to users’ specific requirements, is a key feature to fulfil the diversity of requirements in 5G network. READ MORE

  6. 5. Unsupervised Reinforcement Learning and Downstream Task Finetuning for Simulated Robotics

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Alexander Nöu; [2021]
    Keywords : ;

    Abstract : Deep reinforcement learning algorithms typically require large amounts of data to solve a specific problem, and do not generalize well to other tasks. Recent methods in unsupervised reinforcement learning can learn a range of different behaviors within an environment without the use of task-specific data. READ MORE