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Found 4 papers, 0 papers with code
Reinforcement Learning Under Probabilistic Spatio-Temporal Constraints with Time Windows
We propose an automata-theoretic approach for reinforcement learning (RL) under complex spatio-temporal constraints with time windows.
High Dimensional Robust Consensus over Networks with Limited Capacity
We investigate how robust consensus (small steady state variance of the states) can be achieved within a linear time-invariant setting by optimally assigning edges to state-dimensions.
Edge Augmentation with Controllability Constraints in Directed Laplacian Networks
In this paper, we study the maximum edge augmentation problem in directed Laplacian networks to improve their robustness while preserving lower bounds on their strong structural controllability (SSC).
Probabilistically Guaranteed Satisfaction of Temporal Logic Constraints During Reinforcement Learning
We propose a novel constrained reinforcement learning method for finding optimal policies in Markov Decision Processes while satisfying temporal logic constraints with a desired probability throughout the learning process.
Robotics Systems and Control Systems and Control
