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simulation

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  1. 1

    Some things Veloren does differently

    Veloren’s engine uses a custom ECS, a novel ‘chonks’ voxel storage, full‑world pre‑generation, physically‑based erosion, and a scalable real‑time simulation (rtsim) that keeps tens of thousands of NPCs active, achieving ~50% CPU usage on a 48‑core server with 500+ players.

    Lobstersjsbarretto.com8 minHN5lobste.rs70
  2. 2

    Lucasart's Afterlife

    This blog post revisits Lucasart's 1996 game "Afterlife," a unique SimCity-like game where players manage Heaven and Hell, offering strategies for new and returning players. It details specific game mechanics, zoning tactics, and common pitfalls to help optimize soul collection and progress.

    Hacker News front pagewordpress.com5 minHN10350
  3. 3

    Verifiable Social Reasoning for LLM Assistants

    The paper introduces Fuse, a multi‑agent simulation that gives LLM assistants a verifiable ground‑truth task for social reasoning by hiding a target agent’s motive and letting a user‑mediated conversation infer it. Experiments on 12 LLMs show user mediation makes reasoning harder, models are biased by user framing, need more detail than humans, and longer chats don’t always help.

    Hugging Face Daily Papersarxiv.org1 minpaper
  4. 4

    DeformSmith: Physics Harness-Guided Hierarchical Generation of Deformable Assets for Robot Manipulation

    DeformSmith is a framework that generates physically plausible deformable assets for robot manipulation from a text prompt or a single image, using a hierarchical construction process guided by a shared physics harness. It outperforms prior baselines in visual fidelity and physical realism while also producing interaction data for downstream tasks.

    Hugging Face Daily Papersarxiv.org1 minpaper
  5. 5

    REVERSAL-BENCH: A Reversibility Axis and Reset Oracle for Measuring the Reset-Free RL Cliff

    The paper presents REVERSAL‑BENCH, a benchmark that varies environment reversibility with a parameter ρ and provides a ground‑truth reset oracle for eight manipulation tasks. Using it, the authors show that reset‑free RL agents hit a sharp reversibility cliff and become permanently trapped, while episodic agents remain robust.

    Apple Machine Learning Researchapple.com1 minpaper