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Related Articles from SNS
Constrained Multi-Objective Reinforcement Learning with Max-Min Criterion
arXiv:2605.31388v1 Announce Type: new Abstract: Multi-Objective Reinforcement Learning (MORL) extends standard RL by optimizing policies with respect to multiple, often conflicting, objectives. While max-min MORL has emerged as an effective approach for promoting fairness, its applicability remains limited, particularly when constraints must be incorporated. In this paper, we propose a MORL framework that integrates the max-min criterion with explicit constraint satisfaction.
UA-DCM: Uncertainty-aware Causal Decision Making via Effect Bound Decomposition
arXiv:2601.22736v2 Announce Type: replace Abstract: Causal inference from observational data can provide strong evidence for finding the best action in a decision-making scenario without having to perform expensive randomized trials. The causal effect of an action is often not pointwise identifiable even with infinite data due to unobserved confounding factors. Furthermore, having only finitely many samples adds another layer of uncertainty to causal effect estimation.
Encoded Jamming Secure Communication for RIS-Assisted Systems
Announce Type: replace Abstract: This paper investigates a cooperative jamming (CJ)-aided secure wireless communication system. Conventional CJ schemes transmit Gaussian noise (GN) to improve security, which inherently degrades the legitimate receiver's performance. While encoded jamming (EJ) mitigates this interference, its superiority over GN is highly channel-dependent.