Leveraging Statistical Multi-Agent Online Planning with Emergent Value Function Approximation. - Thomy Phan; Lenz Belzner; Thomas Gabor; Kyrill Schmid (AAMAS, 2018)

Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms. - Thomas Gabor; Lenz Belzner; Thomy Phan; Kyrill Schmid (ICAC, 2018)

Action Markets in Deep Multi-Agent Reinforcement Learning. - Kyrill Schmid; Lenz Belzner; Thomas Gabor; Thomy Phan (ICANN (2), 2018)

Anomaly Detection in Spatial Layer Models of Autonomous Agents. - Marie Kiermeier; Sebastian Feld; Thomy Phan; Claudia Linnhoff-Popien (IDEAL (1), 2018)

Monitoring Autonomous Agents in Self-Organizing Industrial Systems. - Marie Kiermeier; Thomy Phan; Horst Sauer; Jan Wieghardt (INDIN, 2018)

The Sharer's Dilemma in Collective Adaptive Systems of Self-interested Agents. - Lenz Belzner; Kyrill Schmid; Thomy Phan; Thomas Gabor; Martin Wirsing (ISoLA (3), 2018)

Risk-Sensitivity in Simulation Based Online Planning. - Kyrill Schmid; Lenz Belzner; Marie Kiermeier; Alexander Neitz; Thomy Phan; Thomas Gabor; Claudia Linnhoff (KI, 2018)

Memory Bounded Open-Loop Planning in Large POMDPs Using Thompson Sampling. - Thomy Phan; Lenz Belzner; Marie Kiermeier; Markus Friedrich 001; Kyrill Schmid; Claudia Linnhoff-Popien (AAAI, 2019)

Distributed Policy Iteration for Scalable Approximation of Cooperative Multi-Agent Policies. - Thomy Phan; Kyrill Schmid; Lenz Belzner; Thomas Gabor; Sebastian Feld; Claudia Linnhoff-Popien (AAMAS, 2019)

Scenario co-evolution for reinforcement learning on a grid world smart factory domain. - Thomas Gabor; Andreas Sedlmeier; Marie Kiermeier; Thomy Phan; Marcel Henrich; Monika Pichlmair; Bernhard Kempter; Cornel Klein; Horst Sauer; Reiner N. Schmid; Jan Wieghardt (GECCO, 2019)

Subgoal-Based Temporal Abstraction in Monte-Carlo Tree Search. - Thomas Gabor; Jan Peter; Thomy Phan; Christian Meyer; Claudia Linnhoff-Popien (IJCAI, 2019)

Adaptive Thompson Sampling Stacks for Memory Bounded Open-Loop Planning. - Thomy Phan; Thomas Gabor; Robert Müller 005; Christoph Roch; Claudia Linnhoff-Popien (IJCAI, 2019)

Emergent Escape-based Flocking behavior using Multi-Agent Reinforcement Learning. - Carsten Hahn; Thomy Phan; Thomas Gabor; Lenz Belzner; Claudia Linnhoff-Popien (ALIFE, 2019)

Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning. - Andreas Sedlmeier; Thomas Gabor; Thomy Phan; Lenz Belzner; Claudia Linnhoff-Popien (CoRR, 2019)

A Quantum Annealing Algorithm for Finding Pure Nash Equilibria in Graphical Games. - Christoph Roch; Thomy Phan; Sebastian Feld; Robert Müller 005; Thomas Gabor; Claudia Linnhoff-Popien (CoRR, 2019)

Learning and Testing Resilience in Cooperative Multi-Agent Systems. - Thomy Phan; Thomas Gabor; Andreas Sedlmeier; Fabian Ritz; Bernhard Kempter; Cornel Klein; Horst Sauer; Reiner N. Schmid; Jan Wieghardt; Marc Zeller; Claudia Linnhoff-Popien (AAMAS, 2020)

Nash Equilibria in Multi-Agent Swarms. - Carsten Hahn; Thomy Phan; Sebastian Feld; Christoph Roch; Fabian Ritz; Andreas Sedlmeier; Thomas Gabor; Claudia Linnhoff-Popien (ICAART (1), 2020)

Multi-agent Reinforcement Learning for Bargaining under Risk and Asymmetric Information. - Kyrill Schmid; Lenz Belzner; Thomy Phan; Thomas Gabor; Claudia Linnhoff-Popien (ICAART (1), 2020)

Uncertainty-based Out-of-Distribution Classification in Deep Reinforcement Learning. - Andreas Sedlmeier; Thomas Gabor; Thomy Phan; Lenz Belzner; Claudia Linnhoff-Popien (ICAART (2), 2020)

A Quantum Annealing Algorithm for Finding Pure Nash Equilibria in Graphical Games. - Christoph Roch; Thomy Phan; Sebastian Feld; Robert Müller 005; Thomas Gabor; Carsten Hahn; Claudia Linnhoff-Popien (ICCS (6), 2020)

Cross Entropy Hyperparameter Optimization for Constrained Problem Hamiltonians Applied to QAOA. - Christoph Roch; Alexander Impertro; Thomy Phan; Thomas Gabor; Sebastian Feld; Claudia Linnhoff-Popien (ICRC, 2020)

Insights on Training Neural Networks for QUBO Tasks. - Thomas Gabor; Sebastian Feld; Hila Safi; Thomy Phan; Claudia Linnhoff-Popien (ICSE (Workshops), 2020)

The Holy Grail of Quantum Artificial Intelligence: Major Challenges in Accelerating the Machine Learning Pipeline. - Thomas Gabor; Leo Sünkel; Fabian Ritz; Thomy Phan; Lenz Belzner; Christoph Roch; Sebastian Feld; Claudia Linnhoff-Popien (ICSE (Workshops), 2020)

Foraging Swarms using Multi-Agent Reinforcement Learning. - Carsten Hahn; Fabian Ritz; Paula Wikidal; Thomy Phan; Thomas Gabor; Claudia Linnhoff-Popien (ALIFE, 2020)

Towards Ecosystem Management from Greedy Reinforcement Learning in a Predator-Prey Setting. - Fabian Ritz; Felix Hohnstein; Robert Müller 005; Thomy Phan; Thomas Gabor; Carsten Hahn; Claudia Linnhoff-Popien (ALIFE, 2020)

Accelerating Evolutionary Construction Tree Extraction via Graph Partitioning. - Markus Friedrich 001; Sebastian Feld; Thomy Phan; Pierre-Alain Fayolle (CoRR, 2020)

The scenario coevolution paradigm: adaptive quality assurance for adaptive systems. - Thomas Gabor; Andreas Sedlmeier; Thomy Phan; Fabian Ritz; Marie Kiermeier; Lenz Belzner; Bernhard Kempter; Cornel Klein; Horst Sauer; Reiner N. Schmid; Jan Wieghardt; Marc Zeller; et al. (Int. J. Softw. Tools Technol. Transf., 2020)

Resilient Multi-Agent Reinforcement Learning with Adversarial Value Decomposition. - Thomy Phan; Lenz Belzner; Thomas Gabor; Andreas Sedlmeier; Fabian Ritz; Claudia Linnhoff-Popien (AAAI, 2021)

SAT-MARL: Specification Aware Training in Multi-Agent Reinforcement Learning. - Fabian Ritz; Thomy Phan; Robert Müller 005; Thomas Gabor; Andreas Sedlmeier; Marc Zeller; Jan Wieghardt; Reiner N. Schmid; Horst Sauer; Cornel Klein; Claudia Linnhoff-Popien (ICAART (1), 2021)

Specification Aware Multi-Agent Reinforcement Learning. - Fabian Ritz; Thomy Phan; Robert Müller 005; Thomas Gabor; Andreas Sedlmeier; Marc Zeller; Jan Wieghardt; Reiner N. Schmid; Horst Sauer; Cornel Klein; Claudia Linnhoff-Popien (ICAART (Revised Selected Papers), 2021)

A Sustainable Ecosystem through Emergent Cooperation in Multi-Agent Reinforcement Learning. - Fabian Ritz; Daniel Ratke; Thomy Phan; Lenz Belzner; Claudia Linnhoff-Popien (ALIFE, 2021)

VAST: Value Function Factorization with Variable Agent Sub-Teams. - Thomy Phan; Fabian Ritz; Lenz Belzner; Philipp Altmann; Thomas Gabor; Claudia Linnhoff-Popien (NeurIPS, 2021)

Productive fitness in diversity-aware evolutionary algorithms. - Thomas Gabor; Thomy Phan; Claudia Linnhoff-Popien (Nat. Comput., 2021)

Towards Anomaly Detection in Reinforcement Learning. - Robert Müller 005; Steffen Illium; Thomy Phan; Tom Haider; Claudia Linnhoff-Popien (AAMAS, 2022)

Emergent Cooperation from Mutual Acknowledgment Exchange. - Thomy Phan; Felix Sommer; Philipp Altmann; Fabian Ritz; Lenz Belzner; Claudia Linnhoff-Popien (AAMAS, 2022)

Capturing Dependencies Within Machine Learning via a Formal Process Model. - Fabian Ritz; Thomy Phan; Andreas Sedlmeier; Philipp Altmann; Jan Wieghardt; Reiner N. Schmid; Horst Sauer; Cornel Klein; Claudia Linnhoff-Popien; Thomas Gabor (ISoLA (3), 2022)

Attention-Based Recurrency for Multi-Agent Reinforcement Learning under State Uncertainty. - Thomy Phan; Fabian Ritz; Jonas Nüßlein; Michael Kölle 001; Thomas Gabor; Claudia Linnhoff-Popien (AAMAS, 2023)

Attention-Based Recurrence for Multi-Agent Reinforcement Learning under Stochastic Partial Observability. - Thomy Phan; Fabian Ritz; Philipp Altmann; Maximilian Zorn; Jonas Nüßlein; Michael Kölle 001; Thomas Gabor; Claudia Linnhoff-Popien (ICML, 2023)

CROP: Towards Distributional-Shift Robust Reinforcement Learning Using Compact Reshaped Observation Processing. - Philipp Altmann; Fabian Ritz; Leonard Feuchtinger; Jonas Nüßlein; Claudia Linnhoff-Popien; Thomy Phan (IJCAI, 2023)

Adaptive Bi-nonlinear Neural Networks Based on Complex Numbers with Weights Constrained Along the Unit Circle. - Felip Guimerà Cuevas; Thomy Phan; Helmut Schmid (PAKDD (1), 2023)

DIRECT: Learning from Sparse and Shifting Rewards using Discriminative Reward Co-Training. - Philipp Altmann; Thomy Phan; Fabian Ritz; Thomas Gabor; Claudia Linnhoff-Popien (CoRR, 2023)

Challenges for Reinforcement Learning in Quantum Computing. - Philipp Altmann; Adelina Bärligea; Jonas Stein 001; Michael Kölle 001; Thomas Gabor; Thomy Phan; Claudia Linnhoff-Popien (CoRR, 2023)

Emergence and resilience in multi-agent reinforcement learning. - Thomy Phan (2023)

Emergenz und Resilienz in lernenden Multiagentensystemen. - Thomy Phan (Ausgezeichnete Informatikdissertationen, 2023)

Adaptive Anytime Multi-Agent Path Finding Using Bandit-Based Large Neighborhood Search. - Thomy Phan; Taoan Huang; Bistra Dilkina; Sven Koenig (AAAI, 2024)

Quantum Circuit Design: A Reinforcement Learning Challenge. - Philipp Altmann; Adelina Bärligea; Jonas Stein 001; Michael Kölle 001; Thomas Gabor; Thomy Phan; Claudia Linnhoff-Popien (AAMAS, 2024)

Anytime Multi-Agent Path Finding using Operation Parallelism in Large Neighborhood Search. - Shao-Hung Chan; Zhe Chen 016; Dian-Lun Lin; Yue Zhang 048; Daniel Harabor; Sven Koenig; Tsung-Wei Huang; Thomy Phan (AAMAS, 2024)

Confidence-Based Curriculum Learning for Multi-Agent Path Finding. - Thomy Phan; Joseph Driscoll; Justin Romberg; Sven Koenig (AAMAS, 2024)

Aquarium: A Comprehensive Framework for Exploring Predator-Prey Dynamics Through Multi-Agent Reinforcement Learning Algorithms. - Michael Kölle 001; Yannick Erpelding; Fabian Ritz; Thomy Phan; Steffen Illium; Claudia Linnhoff-Popien (ICAART (1), 2024)

Multi-Agent Quantum Reinforcement Learning Using Evolutionary Optimization. - Michael Kölle 001; Felix Topp; Thomy Phan; Philipp Altmann; Jonas Nüßlein; Claudia Linnhoff-Popien (ICAART (1), 2024)

Architectural Influence on Variational Quantum Circuits in Multi-Agent Reinforcement Learning: Evolutionary Strategies for Optimization. - Michael Kölle 001; Karola Schneider; Sabrina Egger; Felix Topp; Thomy Phan; Philipp Altmann; Jonas Nüßlein; Claudia Linnhoff-Popien (ICAART (Revised Selected Paper, 1), 2024)

ClusterComm: Discrete Communication in Decentralized MARL Using Internal Representation Clustering. - Robert Müller 005; Hasan Turalic; Thomy Phan; Michael Kölle 001; Jonas Nüßlein; Claudia Linnhoff-Popien (ICAART (1), 2024)

Challenges for Reinforcement Learning in Quantum Circuit Design. - Philipp Altmann; Jonas Stein 001; Michael Kölle 001; Adelina Bärligea; Maximilian Zorn; Thomas Gabor; Thomy Phan; Sebastian Feld; Claudia Linnhoff-Popien (QCE, 2024)

MEDIATE: Mutually Endorsed Distributed Incentive Acknowledgment Token Exchange. - Philipp Altmann; Katharina Winter; Michael Kölle 001; Maximilian Zorn; Thomy Phan; Claudia Linnhoff-Popien (CoRR, 2024)

Emergent cooperation from mutual acknowledgment exchange in multi-agent reinforcement learning. - Thomy Phan; Felix Sommer; Fabian Ritz; Philipp Altmann; Jonas Nüßlein; Michael Kölle 001; Lenz Belzner; Claudia Linnhoff-Popien (Auton. Agents Multi Agent Syst., 2024)

Counterfactual Online Learning for Open-Loop Monte-Carlo Planning. - Thomy Phan; Shao-Hung Chan; Sven Koenig (AAAI, 2025)

Anytime Multi-Agent Path Finding with an Adaptive Delay-Based Heuristic. - Thomy Phan; Benran Zhang; Shao-Hung Chan; Sven Koenig (AAAI, 2025)

Generative Curricula for Multi-Agent Path Finding via Unsupervised and Reinforcement Learning. - Thomy Phan; Timy Phan; Sven Koenig (J. Artif. Intell. Res., 2025)

New Mechanisms in Flex Distribution for Bounded Suboptimal Multi-Agent Path Finding. - Shao-Hung Chan; Thomy Phan; Jiaoyang Li 001; Sven Koenig (CoRR, 2025)

Multi-Agent Path Finding Among Dynamic Uncontrollable Agents with Statistical Safety Guarantees. - Kegan J. Strawn; Thomy Phan; Eric Wang; Nora Ayanian; Sven Koenig; Lars Lindemann (CoRR, 2025)

Discriminative reward co-training. - Philipp Altmann; Fabian Ritz; Maximilian Zorn; Michael Kölle 001; Thomy Phan; Thomas Gabor; Claudia Linnhoff-Popien (Neural Comput. Appl., 2025)