cs.NE · 2026-10-02 · No. 131

Neural and Evolutionary Computing, 2026-10-02.

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

01 — The papers

2 entries
  1. 01

    TRACE: Tackling Real-World Resource Assignment Problems via Agentic Heuristic Design

    Jose A. Ayala-Romero, Andres Garcia-Saavedra, Xavier Costa-Perez

    cs.NE · cs.LG

    Dynamic resource assignment, the real-time allocation of task streams to heterogeneous processing nodes, is the backbone of modern computing infrastructure. While learning-based schedulers excel in research, industrial deployments still rely on hand-written rules that operators can read, audit, and execute within tight latency budgets. LLM-based Automatic Heuristic Design (AHD) promises to automate writing such rules. However, existing AHD...

    arxiv.org/abs/2610.01887 · PDF

  2. 02

    Continual Reinforcement Learning with Neuroevolution

    Eleni Nisioti, Andrea Cossu, Kathrin Korte, Sebastian Risi

    cs.NE · cs.LG

    Despite many studies about causes and remedies of plasticity loss in Reinforcement Learning (RL) under continual task changes, no RL method has yet consistently achieved a good balance between adaptation and forgetting. Here we turn to an alternative optimization paradigm, neuroevolution (NE): algorithms that search directly in weight space through mutation and selection over a population of neural networks. Across a wide array of...

    arxiv.org/abs/2610.01583 · PDF

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