OpenNovelty.org

Virtual Community: An Open World for Humans, Robots, and Society

ICLR 2026 Conference SubmissionAnonymous Authors
OpenReview Score: 7.3Download Report PDF
embodied AImulti-agentsimulation
Abstract:

The rapid progress of AI and robotics may profoundly transform society, as humans and robots begin to coexist in shared communities, bringing both opportunities and challenges. To explore this future, we present Virtual Community—an open-world platform for humans, robots, and society—built on a universal physics engine and grounded in real-world 3D scenes. With Virtual Community, we aim to enable the study of embodied social intelligence at scale. To support these, Virtual Community features: 1) An open-source multi-agent physics simulator that supports robot, human, and their interactions within a society; 2) A large‑scale, real‑world aligned environment generation pipeline, including vast outdoor space, diverse indoor scenes, and a community of grounded agents with rich characters and appearances. Leveraging Virtual Community, we propose two novel challenges. The Community Planning Challenge evaluates multi‑agent reasoning and planning in open‑world settings, such as cooperating to help agents with daily activities and efficiently connecting other agents. The Community Robot Challenge requires multiple heterogeneous robots to collaborate in solving complex open‑world tasks. We evaluate various baselines and demonstrate the challenges in both high‑level open‑world task planning and low‑level cooperation controls. We have open-sourced our project and hope that Virtual Community will unlock further study of human-robot coexistence in open worlds.

Disclaimer
This report is AI-GENERATED using Large Language Models and WisPaper (A scholar search engine). It analyzes academic papers' tasks and contributions against retrieved prior work. While this system identifies POTENTIAL overlaps and novel directions, ITS COVERAGE IS NOT EXHAUSTIVE AND JUDGMENTS ARE APPROXIMATE. These results are intended to assist human reviewers and SHOULD NOT be relied upon as a definitive verdict on novelty.
NOTE that some papers exist in multiple, slightly different versions (e.g., with different titles or URLs). The system may retrieve several versions of the same underlying work. The current automated pipeline does not reliably align or distinguish these cases, so human reviewers will need to disambiguate them manually.
If you have any questions, please contact: mingzhang23@m.fudan.edu.cn

Overview

Overall Novelty Assessment

The paper introduces Virtual Community, a platform for studying embodied social intelligence through multi-agent interactions in open-world settings. It resides in the Open-World Simulation Platforms leaf of the taxonomy, which contains only two papers: this work and SimWorld. This sparse leaf suggests that comprehensive open-world simulators integrating physics, real-world scene generation, and community-scale agent interactions remain relatively underexplored. The platform's emphasis on human-robot coexistence and society-level dynamics distinguishes it within the broader Benchmarks and Evaluation Platforms branch, which includes more task-specific or dialogue-focused testbeds.

The taxonomy reveals neighboring research directions that contextualize this contribution. The Embodied Multi-Agent Evaluation Platforms leaf contains four papers focused on constrained or task-specific scenarios, while Social Intelligence Benchmarks emphasizes language-based social reasoning without physical grounding. Virtual Community bridges these areas by combining embodied physics simulation with open-world social scenarios. Its real-world scene generation pipeline also connects to the Embodied Agent Architectures branch, where world models integrate physical and social dynamics, though those works typically focus on agent-level cognition rather than platform infrastructure.

Among thirty candidates examined, the automated open-world generation pipeline shows overlap with prior work: two papers provide potentially refutable evidence from ten candidates reviewed. The Virtual Community platform itself and the proposed challenges appear more novel, with zero refutable candidates among ten examined for each contribution. This suggests that while procedural scene generation from geospatial data has precedents, the integrated platform combining physics simulation, community-scale agent populations, and open-world challenges represents a less-explored configuration. The limited search scope means these findings reflect top-thirty semantic matches rather than exhaustive coverage.

Based on the available signals, Virtual Community occupies a sparsely populated research direction within open-world simulation platforms. The taxonomy structure and contribution-level statistics indicate that the platform's integrated approach—combining physics, real-world alignment, and community-scale interactions—addresses gaps in existing infrastructure. However, the analysis is constrained by examining thirty candidates, and the scene generation component shows measurable overlap with prior methods. The platform's novelty appears strongest in its holistic design rather than individual technical components.

Taxonomy

Core-task Taxonomy Papers
50
3
Claimed Contributions
30
Contribution Candidate Papers Compared
2
Refutable Paper

Research Landscape Overview

Core task: embodied social intelligence in open-world multi-agent environments. This field investigates how agents perceive, reason about, and interact with one another in rich, dynamic settings that demand both physical grounding and social understanding. The taxonomy reflects a multifaceted landscape: Multi-Agent Coordination and Collaboration Mechanisms address how agents align goals and share information; Social Reasoning and Theory of Mind explore mental-state inference and perspective-taking (e.g., MuMA-ToM[14], SoMi-ToM[7]); Reinforcement Learning for Multi-Agent Systems develops training paradigms for cooperative or competitive scenarios (Embodied Multi-Agent RL[6]); Embodied Agent Architectures and World Models integrate perception, action, and predictive modeling (Modeling World[13], Social World Model[42]); Benchmarks and Evaluation Platforms provide testbeds ranging from navigation tasks (Social Robot Navigation[3]) to open-ended simulations (Sotopia[4], SimWorld[38]); LLM-Based Agentic Systems and Frameworks leverage large language models for planning and dialogue (Agentic LLMs Survey[5], Ella[9]); Comprehensive Surveys and Taxonomies synthesize progress (Embodied AI Survey[2]); and Specialized Applications and Experimental Platforms tackle domains like argumentation (Argumentation Multi-Agent[1]) or digital societies (Digital Life Project[26]). Several active lines of work highlight contrasting emphases and open questions. One strand focuses on scalable simulation platforms that support diverse agent behaviors and long-horizon interactions, enabling researchers to study emergent social dynamics in controlled yet flexible environments. Another strand prioritizes theory-of-mind capabilities, asking how agents can infer others' beliefs and intentions to enable more nuanced collaboration or competition. Meanwhile, efforts in reinforcement learning and world modeling seek efficient training methods that balance sample complexity with the richness of social cues. Virtual Community[0] sits within the Benchmarks and Evaluation Platforms branch, specifically under Open-World Simulation Platforms, positioning it alongside SimWorld[38] as a testbed for embodied social intelligence. Where SimWorld[38] emphasizes broad environmental diversity, Virtual Community[0] appears to foreground community-level interactions and the interplay of multiple agents in shared spaces, complementing existing benchmarks like Sotopia[4] that focus on dialogue-driven social scenarios. This work thus contributes to the growing infrastructure needed to evaluate and advance agents capable of sophisticated social reasoning in open-world contexts.

Claimed Contributions

Virtual Community platform for multi-agent embodied AI

The authors introduce Virtual Community, a simulation platform that unifies human-like avatars and diverse robots in large-scale, real-world aligned open-world environments. It supports physically realistic multi-agent interactions and is built on the Genesis physics engine.

10 retrieved papers
Automated open-world generation pipeline from real geospatial data

The authors develop an automated pipeline that generates scalable, simulation-ready 3D scenes by refining real-world geospatial data (geometry and texture), placing interactive objects, and creating indoor environments. It also generates agent communities with scene-grounded character profiles and social relationship networks using LLMs.

10 retrieved papers
Can Refute
Community Planning and Community Robot challenges

The authors propose two benchmark challenges to evaluate embodied AI in open-world settings: the Community Planning Challenge for high-level multi-agent reasoning and social influence tasks, and the Community Robot Challenge for low-level physics-based cooperation among heterogeneous robots.

10 retrieved papers

Core Task Comparisons

Comparisons with papers in the same taxonomy category

Contribution Analysis

Detailed comparisons for each claimed contribution

Contribution

Virtual Community platform for multi-agent embodied AI

The authors introduce Virtual Community, a simulation platform that unifies human-like avatars and diverse robots in large-scale, real-world aligned open-world environments. It supports physically realistic multi-agent interactions and is built on the Genesis physics engine.

Contribution

Automated open-world generation pipeline from real geospatial data

The authors develop an automated pipeline that generates scalable, simulation-ready 3D scenes by refining real-world geospatial data (geometry and texture), placing interactive objects, and creating indoor environments. It also generates agent communities with scene-grounded character profiles and social relationship networks using LLMs.

Contribution

Community Planning and Community Robot challenges

The authors propose two benchmark challenges to evaluate embodied AI in open-world settings: the Community Planning Challenge for high-level multi-agent reasoning and social influence tasks, and the Community Robot Challenge for low-level physics-based cooperation among heterogeneous robots.

Table of Contents