IEEE

Probabilistic Constraint for Safety-Critical Reinforcement Learning

Abstract: In this article, we consider the problem of learning safe policies for probabilistic-constrained reinforcement learning (RL). Specifically, a safe policy or controller is one that, with high ...
IEEE

Efficient Solution Validation of Constraint Satisfaction Problems on Neuromorphic Hardware: The Case of Sudoku Puzzles

Abstract: Spiking neural networks (SNNs) offer an effective approach to solving constraint satisfaction problems (CSPs) by leveraging their temporal, event-driven dynamics. Moreover, neuromorphic ...