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Found 4 papers, 2 papers with code
Multi-agent transformer-accelerated RL for satisfaction of STL specifications
One of the main challenges in multi-agent reinforcement learning is scalability as the number of agents increases.
Robust Active Measuring under Model Uncertainty
Partial observability and uncertainty are common problems in sequential decision-making that particularly impede the use of formal models such as Markov decision processes (MDPs).
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes
Autonomous systems are often required to operate in partially observable environments.
Reinforcement Learning with Probabilistic Guarantees for Autonomous Driving
We propose a generic approach to enforce probabilistic guarantees on an RL agent.
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