Microcosmos: Reimagining Artificial Life for the GPU Era

• URL: http://arxiv.org/abs/2607.02954v1
• Date: Fri, 03 Jul 2026 04:58:41 GMT
• Title: Microcosmos: Reimagining Artificial Life for the GPU Era
• Abstract summary: Microcosmos is a simulation engine in which artificial lifeforms are modeled as elastic filament chains inhabiting a two-dimensional viscous fluid world.<n>Hand-designed locomotion strategies confirm that the fluid coupling respects known physical constraints.<n>Neuroevolution and quality-diversity search produce a wide range of swimming and chemotaxis behaviors automatically.
• Score: 3.56395181826838
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Most artificial life simulators either operate on abstract substrates disconnected from physical reality, or simulate physically grounded worlds that do not scale to the population sizes required for open-ended evolution. We present Microcosmos, a simulation engine in which artificial lifeforms are modeled as elastic filament chains inhabiting a two-dimensional viscous fluid world, designed from the ground up for modern GPU hardware and end-to-end differentiable simulation. We validate the engine through four experiments. Hand-designed locomotion strategies confirm that the fluid coupling respects known physical constraints. Gradient-based optimization of filament folding demonstrates both the full differentiability of the simulator and the expressivity of the filament encodings. Neuroevolution and quality-diversity search produce a wide range of swimming and chemotaxis behaviors automatically. Linear scaling with particle count confirms the engine supports large-scale simulation. Microcosmos is released as an open platform with the long-term goal of supporting large-scale open-ended evolutionary simulations, designed to be physically plausible and computationally scalable.

Related papers

• HyperBones: Realtime Bone-driven Neural Garment Simulation with Hypernetwork Conditioning [19.763569928485868]
  We present a fast and physically plausible approach for dynamic garment simulation.<n>Our method trains a reduced-space neural dynamics simulator composed of independent coarse- and fine-level components.<n>Our simulator runs at 300+ FPS on a commodity GPU, making it suitable for real-time applications.
  arXiv  Detail & Related papers  (2026-05-19T20:13:54Z)
• SWoMo: Neuro-Symbolic World Model for Cataract Surgery Simulation [0.7880846345305875]
  We introduce SWoMo, a neuro-symbolic world model for cataract surgery simulation that decouples motion generation from visual realism.<n>We propose an inverse pairing strategy that reconstructs real surgical videos in the simulator to obtain paired simulated and real videos, which are then used to train our video diffusion model.
  arXiv  Detail & Related papers  (2026-05-15T18:27:29Z)
• D-REX: Differentiable Real-to-Sim-to-Real Engine for Learning Dexterous Grasping [66.22412592525369]
  We introduce a real-to-sim-to-real engine that leverages the Gaussian Splat representations to build a differentiable engine.<n>We show that our engine achieves accurate and robust performance in mass identification across various object geometries and mass values.<n>Those optimized mass values facilitate force-aware policy learning, achieving superior and high performance in object grasping.
  arXiv  Detail & Related papers  (2026-03-01T15:32:04Z)
• DiffusionHarmonizer: Bridging Neural Reconstruction and Photorealistic Simulation with Online Diffusion Enhancer [62.18680935878919]
  We introduce DiffusionHarmonizer, an online generative enhancement framework that transforms renderings into temporally consistent outputs.<n>At its core is a single-step temporally-conditioned enhancer capable of running in online simulators on a single GPU.
  arXiv  Detail & Related papers  (2026-02-27T15:35:30Z)
• Hybrid Neural-MPM for Interactive Fluid Simulations in Real-Time [57.30651532625017]
  We present a novel hybrid method that integrates numerical simulation, neural physics, and generative control.<n>Our system demonstrates robust performance across diverse 2D/3D scenarios, material types, and obstacle interactions.<n>We promise to release both models and data upon acceptance.
  arXiv  Detail & Related papers  (2025-05-25T01:27:18Z)
• GausSim: Foreseeing Reality by Gaussian Simulator for Elastic Objects [55.02281855589641]
  GausSim is a novel neural network-based simulator designed to capture the dynamic behaviors of real-world elastic objects represented through Gaussian kernels.<n>We leverage continuum mechanics and treat each kernel as a Center of Mass System (CMS) that represents continuous piece of matter.<n>In addition, GausSim incorporates explicit physics constraints, such as mass and momentum conservation, ensuring interpretable results and robust, physically plausible simulations.
  arXiv  Detail & Related papers  (2024-12-23T18:58:17Z)
• Realistic Surgical Simulation from Monocular Videos [49.114370617718244]
  This paper tackles the challenge of automatically performing realistic surgical simulations from readily available surgical videos.<n>We propose SurgiSim, a novel automatic simulation system to overcome these limitations.<n> Experiments on various surgical scenarios and interactions demonstrate SurgiSim's ability to perform realistic simulation of soft tissues.
  arXiv  Detail & Related papers  (2024-12-03T10:32:41Z)
• DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models [102.13968267347553]
  We present DiffuseBot, a physics-augmented diffusion model that generates soft robot morphologies capable of excelling in a wide spectrum of tasks. We showcase a range of simulated and fabricated robots along with their capabilities.
  arXiv  Detail & Related papers  (2023-11-28T18:58:48Z)
• Inferring Articulated Rigid Body Dynamics from RGBD Video [18.154013621342266]
  We introduce a pipeline that combines inverse rendering with differentiable simulation to create digital twins of real-world articulated mechanisms. Our approach accurately reconstructs the kinematic tree of an articulated mechanism being manipulated by a robot.
  arXiv  Detail & Related papers  (2022-03-20T08:19:02Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.