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ORCIDKyrill Schmid
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2020 – today
- 2024
[c19]Gerhard Stenzel, Kyrill Schmid, Michael Kölle, Philipp Altmann, Marian Lingsch Rosenfeld, Maximilian Zorn, Tim Bücher, Thomas Gabor, Martin Wirsing, Lenz Belzner:
SEGym: Optimizing Large Language Model Assisted Software Engineering Agents with Reinforcement Learning. AISoLA 2024: 107-124- 2023
- [b1]Kyrill Schmid:
Dezentrale Marktmechanismen zur Förderung kooperativen Verhaltens in selbstinteressierten Multiagentensystemen. Ludwig Maximilian University of Munich, Germany, 2023 - [c18]Michael Kölle, Tim Matheis, Philipp Altmann
, Kyrill Schmid:
Learning to Participate Through Trading of Reward Shares. ICAART (1) 2023: 355-362 - [i12]Michael Kölle, Tim Matheis, Philipp Altmann, Kyrill Schmid:
Learning to Participate through Trading of Reward Shares. CoRR abs/2301.07416 (2023) - 2022
- [c17]Tobias Müller, Kyrill Schmid, Daniëlle Schuman, Thomas Gabor, Markus Friedrich, Marc Geitz:
Solving Large Steiner Tree Problems in Graphs for Cost-efficient Fiber-To-The-Home Network Expansion. ICAART (3) 2022: 23-32 - [c16]Tobias Müller, Christoph Roch, Kyrill Schmid, Philipp Altmann:
Towards Multi-agent Reinforcement Learning using Quantum Boltzmann Machines. ICAART (1) 2022: 121-130 - [c15]Xiyue Sun, Fabian R. Pieroth, Kyrill Schmid, Martin Wirsing, Lenz Belzner:
On Learning Stable Cooperation in the Iterated Prisoner's Dilemma with Paid Incentives. ICDCS Workshops 2022: 113-118 - [i11]Kyrill Schmid, Lenz Belzner, Robert Müller, Johannes Tochtermann, Claudia Linnhoff-Popien:
Stochastic Market Games. CoRR abs/2207.07388 (2022) - [i10]Michael Kölle, Lennart Rietdorf, Kyrill Schmid:
Decentralized scheduling through an adaptive, trading-based multi-agent system. CoRR abs/2207.11172 (2022) - 2021
- [c14]Robert Müller, Steffen Illium, Fabian Ritz, Kyrill Schmid:
Analysis of Feature Representations for Anomalous Sound Detection. ICAART (2) 2021: 97-106 - [c13]Kyrill Schmid, Lenz Belzner, Robert Müller, Johannes Tochtermann, Claudia Linnhoff-Popien:
Stochastic Market Games. IJCAI 2021: 384-390 - [c12]Kyrill Schmid, Robert Müller, Lenz Belzner, Johannes Tochtermann, Claudia Linnhoff-Popien:
Distributed Emergent Agreements with Deep Reinforcement Learning. IJCNN 2021: 1-8 - [c11]Kyrill Schmid, Lenz Belzner, Claudia Linnhoff-Popien:
Learning to Penalize Other Learning Agents. ALIFE 2021: 59 - [i9]Tobias Müller, Kyrill Schmid, Daniëlle Schuman, Thomas Gabor, Markus Friedrich, Marc Geitz:
Solving Large Steiner Tree Problems in Graphs for Cost-Efficient Fiber-To-The-Home Network Expansion. CoRR abs/2109.10617 (2021) - [i8]Tobias Müller, Christoph Roch, Kyrill Schmid, Philipp Altmann:
Towards Multi-Agent Reinforcement Learning using Quantum Boltzmann Machines. CoRR abs/2109.10900 (2021) - 2020
- [c10]Kyrill Schmid, Lenz Belzner, Thomy Phan, Thomas Gabor, Claudia Linnhoff-Popien:
Multi-agent Reinforcement Learning for Bargaining under Risk and Asymmetric Information. ICAART (1) 2020: 144-151 - [i7]Robert Müller, Steffen Illium, Fabian Ritz, Kyrill Schmid:
Analysis of Feature Representations for Anomalous Sound Detection. CoRR abs/2012.06282 (2020)
2010 – 2019
- 2019
- [c9]Thomy Phan, Lenz Belzner, Marie Kiermeier, Markus Friedrich, Kyrill Schmid, Claudia Linnhoff-Popien:
Memory Bounded Open-Loop Planning in Large POMDPs Using Thompson Sampling. AAAI 2019: 7941-7948 - [c8]Thomy Phan, Kyrill Schmid, Lenz Belzner, Thomas Gabor, Sebastian Feld, Claudia Linnhoff-Popien:
Distributed Policy Iteration for Scalable Approximation of Cooperative Multi-Agent Policies. AAMAS 2019: 2162-2164 - [c7]Stefan Langer, Robert Müller, Kyrill Schmid, Claudia Linnhoff-Popien:
Difficulty Classification of Mountainbike Downhill Trails Utilizing Deep Neural Networks. PKDD/ECML Workshops (2) 2019: 270-280 - [i6]Thomy Phan, Kyrill Schmid, Lenz Belzner, Thomas Gabor, Sebastian Feld, Claudia Linnhoff-Popien:
Distributed Policy Iteration for Scalable Approximation of Cooperative Multi-Agent Policies. CoRR abs/1901.08761 (2019) - [i5]Thomy Phan, Lenz Belzner, Marie Kiermeier, Markus Friedrich, Kyrill Schmid, Claudia Linnhoff-Popien:
Memory Bounded Open-Loop Planning in Large POMDPs using Thompson Sampling. CoRR abs/1905.04020 (2019) - [i4]Stefan Langer, Robert Müller, Kyrill Schmid, Claudia Linnhoff-Popien:
Difficulty Classification of Mountainbike Downhill Trails utilizing Deep Neural Networks. CoRR abs/1908.04390 (2019) - 2018
- [c6]Thomy Phan, Lenz Belzner, Thomas Gabor, Kyrill Schmid:
Leveraging Statistical Multi-Agent Online Planning with Emergent Value Function Approximation. AAMAS 2018: 730-738 - [c5]Thomas Gabor, Lenz Belzner, Thomy Phan, Kyrill Schmid:
Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms. ICAC 2018: 131-140 - [c4]Kyrill Schmid, Lenz Belzner, Thomas Gabor, Thomy Phan:
Action Markets in Deep Multi-Agent Reinforcement Learning. ICANN (2) 2018: 240-249 - [c3]Lenz Belzner, Kyrill Schmid, Thomy Phan, Thomas Gabor, Martin Wirsing:
The Sharer's Dilemma in Collective Adaptive Systems of Self-interested Agents. ISoLA (3) 2018: 241-256 - [c2]Kyrill Schmid, Lenz Belzner, Marie Kiermeier, Alexander Neitz, Thomy Phan, Thomas Gabor, Claudia Linnhoff:
Risk-Sensitivity in Simulation Based Online Planning. KI 2018: 229-240 - [i3]Thomy Phan, Lenz Belzner, Thomas Gabor, Kyrill Schmid:
Leveraging Statistical Multi-Agent Online Planning with Emergent Value Function Approximation. CoRR abs/1804.06311 (2018) - [i2]Lenz Belzner, Kyrill Schmid, Thomy Phan, Thomas Gabor, Martin Wirsing:
The Sharer's Dilemma in Collective Adaptive Systems of Self-Interested Agents. CoRR abs/1804.10781 (2018) - [i1]Thomas Gabor, Lenz Belzner, Thomy Phan, Kyrill Schmid:
Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms. CoRR abs/1810.12483 (2018) - 2017
- [c1]André Ebert, Kyrill Schmid, Chadly Marouane, Claudia Linnhoff-Popien:
Automated Recognition and Difficulty Assessment of Boulder Routes. HealthyIoT 2017: 62-68
Coauthor Index
aka: Claudia Linnhoff
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