eess.SY · 2026-08-06 · No. 76

Systems and Control, 2026-08-06.

2 new papers in eess.SY. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    ORACLE: A Multi-Objective Reinforcement Learning-Based Analog Circuit Design Optimizer with Large Language Models-Guided Exploration

    Osei Brempong, Mohammed Ayman Habib, Vivan Poddar, Morteza Fayazi

    eess.SY · cs.AI

    Analog circuit design automation using reinforcement learning (RL) has emerged as a promising approach for reducing manual effort. However, many existing RL-based methods focus on single-objective optimization. Even methods designed for multi-objective (MO) problems often reduce multiple design specifications to a single scalar reward. This simplification limits the ability to capture the true Pareto trade-off among competing objectives and...

    arxiv.org/abs/2608.04999 · PDF

  2. 02

    Toward Integrating Adaptive Experience Replay and Online Uncertainty Estimation in Safe Actor-Critic Optimal Control

    Mahshad Rastegarmoghaddam, Davoud Nikkhouy, Shima Samadzadeh

    eess.SY · cs.AI · cs.RO

    Safe actor-critic control often treats barrier filtering, uncertainty estimation, and experience replay as separate modules, even though each changes the data used for learning and control. We develop an integrated architecture in which the uncertainty estimate updates the obstacle geometry used by a control barrier function, filter interventions and estimation residuals determine replay priority, and the critic learns from the executed...

    arxiv.org/abs/2608.04732 · PDF

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