ParallelWorld: Test-Time Scaling for Agentic Embodied Reasoning
Embodied AI has emerged as a key paradigm for autonomous systems operating in complex physical environments. While end-to-end models have established strong local capabilities for perception and control, scaling these capabilities to extended, multi-stage tasks remains difficult. Agentic embodied systems address this challenge by introducing high-level planners that organize perception, reasoning, and executable skills over longer interaction horizons. However, existing agentic embodied frameworks typically generate actions for direct execution without explicitly simulating how alternative action sequences shape future observations and task progress, leading agents to commit to suboptimal...
| Authors | Min Chen, Shengjun Zhang, Yuxin Li et al. |
|---|---|
| Primary category | cs.AI |
| Published | 24 August 2026 |
| Last updated at source | 13 October 2026 |
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