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Michael Girstl: Safe Reinforcement learning using Successor representations

Posted by By mugga May 4, 2025Posted inFinished, Project, Student-Projects, Uncategorized
Reinforcement Learning (RL) has achieved remarkable success in various domains, from game playing to robotics. However, in safety-critical applications such as autonomous driving or medical treatment, traditional RL algorithms may…
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Haris Asif: Quantum Circuit Optimization via Hierarchical Reinforcement Learning (FAU Erlangen-Nürnberg, 2024)

Posted by By mugga May 4, 2025Posted inFinished, Master Thesis, Student-Projects
Motivation / Related Work Optimizing quantum circuits is essential for various applications, such as chemical simulations, due to the inherent complexity of quantum systems and the current limitations of quantum…
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Thorsten Bescher: Schedule-Net and Gumbel-Alpha-Zero Play-to-Plan: a Hybrid Approach for the Job-Shop Scheduling Problem (FAU Erlangen-Nürnberg, 2024)

Posted by By mugga May 4, 2025Posted inFinished, Master Thesis, Student-Projects
Motivation / Related Work Recently, reinforcement learning (RL) is applied frequently for combinatorial optimization problems [1] with real world applications, e.g., the job-shop scheduling problem (JSSP) or the travelling salesman…
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Stephan Geisler: Designing and training foundation models for positioning applications (FAU Erlangen-Nürnberg, 2024)

Posted by By mugga May 4, 2025Posted inFinished, Master Thesis, Student-Projects
Foundation models (like OpenAI’s GPT-4/ChatGPT [1] or Meta’s Llama 2 [2]) have been a disruptive technology that within just few months has started to transform the modus operandi of several industries. There have…
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Nicolas Kolbenschlag: Automated Generation of Block-Encodings for Quantum Policy Iteration (FAU Erlangen-Nürnberg, 2024)

Posted by By mugga May 4, 2025Posted inFinished, Master Thesis, Student-Projects
Motivation The rise of quantum computing has offered new opportunities to achieve computational tasks that classical computers cannot. However, to achieve quantum advantage over classical algorithms, it is necessary to…
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Alexander Mattick: Reinforcement Learning for Node Selection in Branch-and-Bound (FAU Erlangen-Nürnberg, 2023)

Posted by By mugga May 4, 2025Posted inFinished, Master Thesis, Student-Projects
1 Introduction The branch-and-bound algorithm is a fundamental solver for linear mixed integer programming problems. It is used to solve optimization problems with a combination of continuous and integer variables.…
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Yongxu Ren: Variational Quantum Compiling with (Deep) Reinforcement Learning (FAU Erlangen-Nürnberg, 2023)

Posted by By mugga November 1, 2022Posted inFinished, Master Thesis, Student-Projects, Uncategorized
MotivationQuantum computing promises to revolutionize many areas that are hard or impossible to approach with tra- ditional computers. However, due to rigid hardware restrictions and noise sensitivity of currently available…
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Alexander Mattick: Beam Tracking as a Time-Varying Reinforcement Learning Problem

Posted by By mugga November 1, 2022Posted inFinished, Project, Student-Projects, Uncategorized
The envisioned transition to 5G and 6G technologies have started to transform the properties of established communication networks. In the core of this transformation lies the capability of Base Stations…
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Abhinav Singh: Safe Imitation Learning for Beam Tracking

Posted by By mugga November 1, 2022Posted inFinished, Project, Student-Projects, Uncategorized
The envisioned transition to 5G and 6G technologies have started to transform the properties of established communication networks. In the core of this transformation lies the capability of Base Stations…
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Lukas Frieß: Model-based Reinforcement Learning with First-Principle Models (FAU Erlangen-Nürnberg, 2021)

Posted by By mugga May 2, 2022Posted inFinished, Master Thesis, Student-Projects, Uncategorized
Motivation Reinforcement learning (RL) is increasingly used in robotics to learn complex tasks from repeated interactions with the environment. For example, a mobile robot can learn to avoid an obstacle…
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