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Subject heading

Allgemeinbegriff

Bestärkendes Lernen (Künstliche Intelligenz)

Maschinelles Lernen

Subject heading

Bestärkendes Lernen (Künstliche Intelligenz)

Definition

Lernmethode (Maschinelles Lernen), die einem Agenten (Künstliche Intelligenz) oder einem zu trainierenden künstlichen neuronalem Netz kein explizites Lernziel vorgibt, sondern dem Agenten/Netz nach jeder Aktion nur mitteilt, ob diese Aktion als gut oder schlecht befunden wird.

Synonym

Reinforcement Learning (Künstliche Intelligenz) (Wikipedia (engl.))
Reinforcement-Lernen (Künstliche Intelligenz) (Spektrum Lex. Neurowiss.)
Verstärkendes Lernen (Künstliche Intelligenz) (Informatik-HB)
Verstärkungslernen (Künstliche Intelligenz)

Broader term

Maschinelles Lernen

Topic

Informatik, Datenverarbeitung

Source

Wikipedia

Record type

Allgemeinbegriff

GND-Identifier

4825546-4

Record ID

974538477

Topic of

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Beyond trial and error : improving reinforcement learning through representation learning and reasoning

Data-driven Optimization using Deep Reinforcement Learning with Applications in Semiconductor Testing and Digital Healthcare

Deep Reinforcement Learning zur Maximierung des Gewinns eines Würfelspiels

Evaluation der Herausforderungen im Erstellungsprozess eines dynamisch reagierenden Machine Learning-Agenten für den Einsatz in Videospielen

Intelligent Virtual Agents in Primary Education: Investigating Adaptive Mechanisms in a Digital Reading Intervention Using Reinforcement Learning

Prädiktive Sicherheitszonen in der Mensch-Roboter-Kollaboration mittels Reinforcement Learning und LSTM

Safe Reinforcement Learning for Robotics

3D-Simulation und prototypischer Aufbau eines durch Reinforcement Learning gesteuerten Labyrinths

Automatische Beurteilung situationsbezogener Risiken von mobilen Industrierobotern

Automatische Beurteilung situationsbezogener Risiken von mobilen Industrierobotern

Automatisiertes Testen mobiler Applikationen mit Hilfe von Large Language Models und Reinforcement Learning

Autonomous View Planning using Reinforcement Learning - Modeling and Application for Visual Inspection in Remanufacturing

Autonomous view planning using reinforcement learning : modeling and application for visual inspection in remanufacturing

Autonomous View Planning using Reinforcement Learning : Modeling and Application for Visual Inspection in Remanufacturing

Battery aging-aware vehicle-to-grid control in home charging systems via deep reinforcement learning

Bedarfsgesteuerte Abtauung von Luft-Wärmepumpen durch Reinforcement Learning

Bestärkendes Lernen zur automatisierten Erkundung und Kartographierung von Indoor-Umgebungen mittels unbemanntem Luftfahrtsystem

Cerebellar Contributions to Prediction Error Processing in Reinforcement Learning

Data-efficient reinforcement learning with Bayesian neural networks

Deep Reinforcement Learning in Communication Systems – Addressing Partial Observability in Decentralized Multi-Agent Systems with Learned Communication

Deep Reinforcement Learning zum maschinellen Erlernen von Strategien zur Lösung von Zauberwürfeln

Dynamic approaches for stochastic gradient methods in reinforcement learning

Dynamische Sicherheitszonen mit LSTM und Deep Reinforcement Learning für kollaborative Roboter : Eine simulationsbasierte Untersuchung

End-to-end reinforcement learning of koopman model predictive control

Entwicklung einer Methode zum Einsatz von Multi-Agent Reinforcement Learning für die virtuelle Verdrahtung im 3D-CAD

Entwicklung eines KI gesteuerten Tischkickers unter Verwendung von Reinforcement Learning

Environment Design for Learning the Optimal Power Flow with Reinforcement Learning

Essays on deep reinforcement learning with applications to path planning and control of autonomous vehicles

Generalisierungseigenschaften eines Multi- Agenten-Reinforcement-Learning-Ansatzes zur Steuerung von Portalrobotern

Imaging satellites task planning : learning-based BI-level models and algorithms

Imaging Satellites Task Planning : Learning-Based BI-Level Models and Algorithms

Inverse Reinforcement Learning for Human Decision-Making Under Uncertainty

Kollisionsfreie lokale Roboternavigation mit Deep Reinforcement Learning in statischen und dynamischen Umgebungen

Learning in Non-Stationary Environments

Learning tree-based models with gradient descent

Learning Versatile Skills using Reinforcement Learning

Machine learning methods for injection optimization at the cooler synchrotron COSY

Mechanisms of reinforcement learning and decision making in different environments

Model-based reinforcement learning with state-space models

Modeling electricity markets with multi-agent deep reinforcement learning

Modular transfer reinforcement learning in industrial robotics

Multi-agent reinforcement learning for deadlock handling among autonomous mobile robots

Novel textile reinforcements with integrated textile-based in-situ sensors for the reinforcement of existing concrete structures against short-term dynamic events

Optimization of Power-to-Gas system operation and dispatch using Deep Reinforcement Learning

Physics-informed machine learning for virtual inertia provision from distribution power systems

Physics-informed Machine Learning for Virtual Inertia Provision from Distribution Power Systems

Probabilistic World and Behavior Models for Embodied Agents

Real-time reinforcement learning with online training for large-scale facilities

Reinforcement Learning and Differentiable Simulations for Autonomous Tuning and Control of Linear Particle Accelerators

Reinforcement learning for real-world production systems

Reinforcement Learning in automobilen In-the-loop-Anwendungen

Reinforcement Learning with Guarantees

Reinforcement learning-based optimization of the job shop problem with transportation resources

Reinforcement Learning-Based Worst-Case Analysis for Flight Control Clearance

Robustness of reinforcement learning based autonomous driving technologies

Rocket engine control with deep reinforcement learning

Safe Reinforcement Learning for Robotics: From Exploration to Policy Learning

Selbstlernende Spurregelung von Flurförderzeugen unter Verwendung Künstlicher Intelligenz

Selbstorganisation, Selbstausrichtung und Selbstanpassung in lernenden Multi-Agenten-Systemen

Supervised and reinforcement learning for the development and optimization of H₂-engines
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