22 citations · 83 across the 32 of their papers we have counts for
42 papers
Sample-Efficient Policy Space Response Oracles with Joint Experience Best Response
Ariyan Bighashdel, Thiago D. Simão, Frans A. Oliehoek
Multi-agent reinforcement learning (MARL) offers a scalable alternative to exact game-theoretic analysis but suffers from non-stationarity and the need to maintain diverse populati…
Learning to Focus: Prioritizing Informative Histories with Structured Attention Mechanisms in Partially Observable Reinforcement Learning
Daniel De Dios Allegue, Jinke He, Frans A. Oliehoek
Transformers have shown strong ability to model long-term dependencies and are increasingly adopted as world models in model-based reinforcement learning (RL) under partial observa…
Conditional Policy Generator for Dynamic Constraint Satisfaction and Optimization
Wook Lee, Frans A. Oliehoek
Leveraging machine learning methods to solve constraint satisfaction problems has shown promising, but they are mostly limited to a static situation where the problem description i…
Timing the Match: A Deep Reinforcement Learning Approach for Ride-Hailing and Ride-Pooling Services
Yiman Bao, Jie Gao, Jinke He +2
Efficient timing in ride-matching is crucial for improving the performance of ride-hailing and ride-pooling services, as it determines the number of drivers and passengers consider…
SHARPIE: A Modular Framework for Reinforcement Learning and Human-AI Interaction Experiments
Hüseyin Aydın, Kevin Godin-Dubois, Libio Goncalvez Braz +6
Reinforcement learning (RL) offers a general approach for modeling and training AI agents, including human-AI interaction scenarios. In this paper, we propose SHARPIE (Shared Human…
SimuDICE: Offline Policy Optimization Through World Model Updates and DICE Estimation
Catalin E. Brita, Stephan Bongers, Frans A. Oliehoek
In offline reinforcement learning, deriving an effective policy from a pre-collected set of experiences is challenging due to the distribution mismatch between the target policy an…