Publications by Schmid, Kyrill

Journal article

Schmid, Kyrill; Belzner, Lenz; Phan, Thomy; Gabor, Thomas; Linnhoff-Popien, Claudia (2020): Multi-agent Reinforcement Learning for Bargaining under Risk and Asymmetric Information. In: Icaart: Proceedings of the 12Th International Conference on Agents and Artificial Intelligence, Vol 1: pp. 144-151

Phan, Thomy; Schmid, Kyrill; Belzner, Lenz; Gabor, Thomas; Feld, Sebastian; Linnhoff-Popien, Claudia (2019): Distributed Policy Iteration for Scalable Approximation of Cooperative Multi-Agent Policies. In: Aamas '19: Proceedings of the 18Th International Conference on Autonomous Agents and Multiagent Systems: pp. 2162-2164

Phan, Thomy; Belzner, Lenz; Kiermeier, Marie; Friedrich, Markus; Schmid, Kyrill; Linnhoff-Popien, Claudia (2019): Memory Bounded Open-Loop Planning in Large POMDPs Using Thompson Sampling. In: Thirty-Third Aaai Conference on Artificial Intelligence / Thirty-First Innovative Applications of Artificial Intelligence Conference / Ninth Aaai Symposium on Educational Advances in Artificial Intelligence: pp. 7941-7948

Gabor, Thomas; Belzner, Lenz; Phan, Thomy; Schmid, Kyrill (2018): Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms. In: 15Th Ieee International Conference on Autonomic Computing (Icac 2018): pp. 131-140

Schmid, Kyrill; Belzner, Lenz; Gabor, Thomas; Phan, Thomy (2018): Action Markets in Deep Multi-Agent Reinforcement Learning. In: Artificial Neural Networks and Machine Learning - Icann 2018, Pt Ii, Vol. 11140: pp. 240-249

Book Section

Schmid, Kyrill; Ritz, Fabian; Illium, Steffen; Müller, Robert (2021): Analysis of Feature Representations for Anomalous Sound Detection. In: Proceedings of the 13th International Conference on Agents and Artificial Intelligence (Volume 2). ICAART, Setúbal, Portuagl: SciTePress. pp. 97-106

Conference or Workshop Item

Schmid, Kyrill; Müller, Robert; Belzner, Lenz; Tochtermann, Johannes; Linnhoff-Popien, Claudia (2021): Distributed Emergent Agreements with Deep Reinforcement Learning. 2021 International Joint Conference on Neural Networks (IJCNN), 18-22 July 2021, Shenzhen, China.